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Senior Data Engineer

Leidos

Location: Remote — Worldwide Advertised pay: USD 107,900–195,050 / yearly Work arrangement: Worldwide remote Employment: Full Time Posted: November 9, 2026 Freshness: Posted today Source check: Observed today
Disclosure5 of 5 core facts statedReview uncertainties
Last source observationObserved todayObservation is not employer confirmation.
Application destinationhimalayas.appReview the application route and source evidence in the full report below.

Executive opportunity brief

The decision in one screen

A compact evidence-first read of compensation, flexibility, mobility and what still needs verification. No universal quality score is used.

Compensation positionBelow the current median94 current same-currency observations
Work flexibilityWorldwide remoteBased only on stated location/work-arrangement evidence.
Decision evidence5 of 5 core facts knownThis listing states more core decision facts than the median role in the current sample.
Mobility evidenceSponsorship not establishedUnknown evidence is not treated as unavailable.
Current alternatives1237 current same-family rolesCurrent HPJ inventory, not the whole labor market.
Negotiation readinessNegotiation evidence available: advertised pay range, current same-currency market context, strong decision evidence.Use the private Offer & Negotiation Lab below if an offer arrives.

Fast read

Opportunity DNA

What stands out most is that location flexibility looks unusually broad. The biggest counterweight is that the experience requirement raises the entry bar.

May appeal in aRemote-first search
PayRange available

Current comparable position is around the 36th percentile.

FlexibilityBroad location freedom

No material geography, office-attendance or timezone restriction is visible in the available wording.

Entry pathHigher entry bar

One or more material qualification requirements are stated and may narrow the realistic applicant pool.

MobilityNot established

Sponsorship and relocation support are not clear from the current listing.

ApplicationSome process detail

Part of the application route can be assessed, but the full external process may contain additional steps.

TraceabilityCurrent source traceable

At least one recent enabled source can still renew this vacancy.

This fingerprint summarizes what is clear, constrained or still unanswered in the current listing. It is a reading aid, not an overall job score.

Decision evidence check

5 of 5 core facts stated

This checks whether the listing states the facts that commonly change an employment decision. It measures disclosure completeness, not whether the opportunity is good or bad.

Facts already stated

  • Compensation
  • Work arrangement
  • Advertised location
  • Application closing time
  • Employment type

Core evidence complete

All five core facts are stated. Other details can still matter, so continue with the qualification, mobility, employer and application checks below.

Advertised location is not proof of work authorization, sponsorship, or legal eligibility. Unknown information is not a negative score; verify those questions separately.

Decision levers

What could make or break the fit?

Reasons to look closer

  • Location flexibility looks unusually broad: The available wording supports high Remote Freedom without a material geography, office-attendance or timezone restriction showing up.

Trade-offs to weigh

  • The experience requirement raises the entry bar: The listing appears to require at least about 10 years of experience.

Questions worth asking before you invest more time

  • Confirm whether a degree is actually required, preferred, or replaceable with equivalent experience.
  • Ask whether visa sponsorship is available before investing significant time in the application.

These questions come from details the listing leaves open. An unanswered point is not treated as a disadvantage.

Opportunity neighborhood

Keep your options open

These live roles sit close enough to this opportunity to make useful comparison points. Look across several employers before deciding what pay, flexibility or access trade-offs you are willing to accept.

Senior Machine Learning Engineer, Ranking - Quora

Quora · Canada, Ireland, USA

USD 189,507–274,604 / year Region-restricted remote 4/5 core facts

Why it is nearby: Same seniority band · Similar work arrangement · Same employment type

About 53% higher advertised midpoint

Sr. Staff Machine Learning Systems Engineer

hims & hers · USA

USD 240,000–265,000 / year Region-restricted remote 4/5 core facts

Why it is nearby: Same seniority band · Similar work arrangement · Same employment type

About 67% higher advertised midpoint

Senior Data Engineer

LendingTree · USA

USD 100,000–130,000 / year Region-restricted remote 4/5 core facts

Why it is nearby: Same seniority band · Similar work arrangement · Same employment type

About 24% lower advertised midpoint

Principal Data Scientist, User Ecosystem

Reddit · USA

USD 313,000–365,100 / year Region-restricted remote 4/5 core facts

Why it is nearby: Same seniority band · Similar work arrangement · Same employment type

About 124% higher advertised midpoint

This neighborhood is drawn from current inventory in the same broad occupation. Similarity is based on explicit listing facts; missing details do not count against a job.

Role market context

How much current choice is visible around this kind of work?

This compares the vacancy with current High Paid Job inventory in the broad Data & AI roles family. It describes visible choice and disclosure, not future demand or career quality.

Current visible roles1,237

200 most recent current roles sampled for the disclosure measures below.

Employers represented141

Distinct employers in the bounded current sample, not an estimate of all employers hiring in the market.

Decision-ready disclosure36%

Current sampled roles stating at least four of the five Core Decision Facts.

Compensation stated37%

Requires a numeric amount, explicit ISO currency and supported pay period.

Work arrangement stated91%

Listings with explicit enough remote, hybrid or on-site evidence to classify.

Stated closing time24%

Missing deadline evidence remains unknown and is not interpreted as an open-ended application window.

Disclosure comparison: This listing states more core decision facts than the median role in the current sample. This listing: 5/5 · sample median: 3.0/5.

Currencies with explicit pay evidence in the sample: USD (60) · EUR (8) · GBP (4) · CAD (1). Raw amounts across different currencies are not compared.

This describes current visible High Paid Job inventory in the same broad occupation family. Percentages use a bounded recent sample and are not a forecast, a complete labor-market census or an employer-quality measure.

Constraint opportunity lab

What changes the size of the current opportunity pool?

Each line applies one stricter evidence-based constraint to the same bounded current role-family sample. It helps you see the trade-off in visible choice without deciding which trade-off is right for you.

Require explicit sponsorship or relocation support 0 / 200 0%

Counts only affirmative or possible sponsorship evidence, or relocation explicitly offered. Unknown is not treated as no.

Require worldwide remote evidence 17 / 200 9%

A much stricter subset: only listings with explicit worldwide-remote evidence remain.

Require a remote-listed arrangement 63 / 200 32%

Counts roles explicitly classified as worldwide remote, region-restricted remote or remote with restrictions still unclear.

Require at least four Core Decision Facts 72 / 200 36%

Shows the subset with enough stated evidence for a more informed first comparison.

Require usable compensation disclosure 73 / 200 37%

Requires amount, explicit ISO currency and a supported pay period. Missing pay evidence remains unknown.

Keep this advertised salary floor in the same currency 46 / 59 78%

Only same-currency opportunities with usable annualized pay enter this comparison. Other currencies are not converted or treated as lower.

Keep the same employment type 127 / 136 93%

Uses only roles with a stated employment type.

Stay around the same seniority band 185 / 200 93%

Includes roles whose seniority is genuinely unspecified rather than assuming they belong to another level.

These are counterfactual filters over a bounded sample of current HPJ inventory in the same broad occupation family. They show how visible choice changes when one evidence-based constraint is applied; they do not tell you which constraint you should choose or predict hiring outcomes. The calculation uses the 200 most recent current roles from 1237 visible roles in this broad family.

Salary transparency context

Is pay disclosure typical for this kind of role?

This listing states usable structured compensation. About 37% of the bounded current role sample does the same.

This listingUsable pay stated

Compensation counts only when amount, ISO currency and supported pay period are all known.

Current same-role sample37%

Pay disclosure is limited in the current role sample.

Current employer pattern100%

This employer’s current visible listings disclose pay materially more often than the current same-role sample.

This compares salary-disclosure behavior in current visible listings. It does not compare raw salary amounts across currencies, infer undisclosed pay as zero, or rate employer quality.

Private offer & negotiation lab

Turn an offer into evidence, not guesswork

Enter an annual base offer and, if you want, your own target. HPJ compares only within one explicit currency and never chooses a target for you.

Advertised annualized payUSD 107,900–195,050 / yearListing evidence only.
Current comparable medianUSD 170,00055 current sampled roles
Current upper quartileUSD 239,378Current HPJ inventory context, not a salary recommendation.

Negotiation evidence available: advertised pay range, current same-currency market context, strong decision evidence.

Enter an annual base offer to compare it with explicit same-currency evidence. HPJ will not suggest a target for you.

Review the full package · 10 terms

Mark what is confirmed, what needs clarification and what you want to prioritize. These choices and notes stay in this browser.

Base payKnown

Usable advertised compensation is available.

Bonus / commissionVerify

Variable compensation is mentioned; verify amount, formula, target and eligibility.

Equity / long-term incentivesMentioned

Equity or long-term incentive language is mentioned; verify grant type, vesting and valuation basis.

Retirement / pensionVerify

Retirement or pension benefits are mentioned; verify employer contribution and vesting.

Health benefitsVerify

Health-benefit language is mentioned; verify coverage, dependants and employee cost.

Paid leaveVerify

Paid-leave language is mentioned; verify the exact entitlement and carry-over rules.

Work arrangementKnown

A work-arrangement signal is available; verify schedule details before relying on it.

RelocationVerify

Relocation support not established

Visa / work authorizationVerify

Sponsorship not established

Review timingVerify

A review cycle is mentioned; verify timing and whether compensation can change at that review.

Questions worth taking into the offer conversation

  • Is there a bonus, commission or other variable-pay component, and how is it calculated?
  • What retirement or pension contribution does the employer provide?
  • What health coverage is included and what costs remain with the employee?
  • How much paid leave is provided and what are the carry-over or blackout rules?
  • If relocation is relevant, what expenses, timing and repayment conditions are covered?
  • What exact sponsorship or work-authorization conditions apply to this role?
  • When is the first performance and compensation review after joining?

Occupation intelligence

What broader career references connect to this role?

HPJ uses broad comparison families for current-market analysis. External taxonomy results are reference candidates for that broad family, not a declaration that this vacancy has been authoritatively classified into a specific occupation.

HPJ comparison familyData & AI roles
Adjacent families worth exploringSoftware engineering roles · Product roles

European occupation references

This service uses the ESCO classification of the European Commission.

U.S. occupation references

This site incorporates information from O*NET Web Services by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). O*NET® is a trademark of USDOL/ETA.

Career reference research

Skills worth investigating

Official occupational context, paired with exact phrases visible in this vacancy. It is not a skills test or an applicant-fit score.

ESCO · European occupation

data scientist

Usually essential in this ESCO occupation
  • handle data samples
  • integrate gender dimension in research
  • deliver visual presentation of data
  • scientific literature
  • promote the participation of citizens in scientific and research activities
  • perform data cleansing
  • manage intellectual property rights
Context-dependent ESCO skills
  • MDX
  • scientific computing
  • digital curation
  • integrate ICT data
  • state estimation

O*NET · U.S. occupation

Data Scientists

O*NET occupation skills
  • Mathematics
  • Critical Thinking
  • Reading Comprehension
  • Complex Problem Solving
  • Programming
  • Active Learning
  • Speaking
  • Active Listening
Build my private skill preparation brief Your evidence · Practice · Interview questions

Plan how you might demonstrate or investigate occupational skills. These are broad-family reference examples, not confirmed vacancy requirements. Nothing you enter is sent to High Paid Job.

handle data samplesESCO · Essential · Listing mention unknown
integrate gender dimension in researchESCO · Essential · Listing mention unknown
deliver visual presentation of dataESCO · Essential · Listing mention unknown
scientific literatureESCO · Essential · Listing mention unknown
promote the participation of citizens in scientific and research activitiesESCO · Essential · Listing mention unknown
perform data cleansingESCO · Essential · Listing mention unknown
manage intellectual property rightsESCO · Essential · Listing mention unknown
MDXESCO · Optional · Listing mention unknown
scientific computingESCO · Optional · Listing mention unknown
digital curationESCO · Optional · Listing mention unknown
integrate ICT dataESCO · Optional · Listing mention unknown
state estimationESCO · Optional · Listing mention unknown
MathematicsO*NET · Skills · Listing mention unknown
Critical ThinkingO*NET · Skills · Listing mention unknown
Reading ComprehensionO*NET · Skills · Listing mention unknown
Complex Problem SolvingO*NET · Skills · Listing mention unknown
ProgrammingO*NET · Skills · Listing mention unknown
Active LearningO*NET · Skills · Listing mention unknown
SpeakingO*NET · Skills · Listing mention unknown
Active ListeningO*NET · Skills · Listing mention unknown

Private to this browser. Up to 20 reference skills; not a qualification assessment or hiring prediction.

Useful next question: Which of these occupational reference skills does the hiring manager actually expect for this specific role, and what evidence would demonstrate them?

These skills belong to one reference occupation selected for HPJ’s broad career family, not a verified classification of this vacancy. Text overlap only means a phrase appears in the available listing text; it does not establish an employer requirement, your proficiency, or a qualification gap. A missing mention is unknown, not a deficit.

Adjacent current roles to investigate

Product roles

Payment Product Manager (Fiat)

Binance · Hong Kong, Singapore

same seniority band · same employment type · similar work-arrangement evidence

Adjacent-family roles are exploration prompts from current HPJ inventory. They are not inferred qualification matches and they do not imply a promotion path.

Career move map

What sits one step away?

This listing is currently read as Senior / lead. Nearby roles one visible seniority step away can help you judge whether to widen the search, stretch upward or compare the responsibilities more carefully.

Broader-entry direction

Mid-career

FBS Associate Data Engineer

Capgemini Technology Services · Remote — Worldwide

Similar work arrangement · Same employment type · Recently posted

Stretch direction

Leadership

Lead Data Analyst

Liftoff · USA

Similar work arrangement · Same employment type · Recently posted Advertised midpoint is about 11% higher

These are live roles one visible seniority step away in the same broad occupation family. They can reveal nearby options, but they are not a guaranteed promotion path and do not account for your personal experience.

Skill bridge

What does this role connect to?

AWS is one of the signals this listing shares with skills appearing often across current Data & AI roles opportunities.

Skills named in this listing

AgileAWSAzureDatabricksGoogle CloudPythonSQL

Shared with the current career sample

  • AWS Seen in 35 sampled listings
  • Azure Seen in 20 sampled listings
  • Databricks Seen in 24 sampled listings
  • Google Cloud Seen in 17 sampled listings

Combinations also appearing together

  • Python + SQL appeared together in 57 sampled listings
  • AWS + Python appeared together in 29 sampled listings
  • AWS + SQL appeared together in 21 sampled listings

Additional signals in this listing: Agile

Application edge

  • If these skills match your background, prepare one concrete example that shows how you used Agile, AWS, and Azure rather than relying on a keyword-only claim.
  • The listing states about 10 years of required experience. Check that the dates and scope in your application make that experience easy to verify.

If the named skills are genuinely transferable in your own experience, the occupation map also points to adjacent current families worth researching: Software engineering roles and Product roles. This is exploration context, not a qualification match.

Skill signals come from explicit text mentions. A mention is not automatically a requirement, and absence from the current top-skill list does not make a skill rare or unimportant. The current career comparison draws on 120 sampled listings; 119 contain a recognized skill signal.

Application Decision Lab

Turn the listing into a preparation plan

Separate what the listing actually states from what you still need to prepare or verify. Your selections and short notes stay in this browser and are never submitted to High Paid Job.

Explicit requirement

At least about 10 years of experience required

The available wording contains an explicit minimum/required years-of-experience signal. Preferred years are tracked separately and never promoted into the required minimum.

Listing mention

Agile

This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.

Listing mention

AWS

This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.

Listing mention

Azure

This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.

Listing mention

Databricks

This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.

Listing mention

Google Cloud

This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.

Listing mention

Python

This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.

Questions worth resolving before you rely on the opportunity

  • Work authorization / sponsorship: If sponsorship or work authorization matters to you, what exact immigration or employer-sponsorship conditions apply to this role?
  • Application process: What interview, assessment, portfolio, reference or screening stages are part of the hiring process?

Decision analysis

What the listing really tells you

Rich decision context

A closer look at Senior Data Engineer at Leidos points most strongly to pay has a useful comparison point, the location rules are clear enough to judge, and qualifications reveal more than the job title alone. Those signals shape the practical upside and the questions still worth asking.

Pay has a useful comparison point

The annualized midpoint sits near the 36th percentile within 94 comparable USD salary observations. Treat that as current advertised-pay context rather than a forecast of take-home or total compensation.

The location rules are clear enough to judge

The work-location pattern is “Highly location-flexible”, with Remote Freedom at 96/100.

Qualifications reveal more than the job title alone

At least about 10 years of experience required · 1 additional stated barrier. Unstated education or experience requirements stay open rather than being assumed.

The application route gives a few useful clues

Provider-mediated application path. The external application may contain additional steps that are not visible from the listing itself.

Source continuity adds useful context

1 recent enabled source can currently renew this vacancy across 1 source classes. That improves traceability, although it does not verify the employer itself.

How this analysis is assembled

This read combines the structured details currently available for pay, flexibility, qualifications, mobility, application effort and source continuity. Missing facts are left open for you to verify.

Analysis evidence coverage

How much analysis can the current evidence support?

100%Strong analysis evidence coverage
100%
Current-sample pay position36 / 100

Uses the explainable High Pay Score within the job’s current occupation/seniority/currency comparison sample.

Remote Freedom evidence96 / 100

Measures observable location flexibility and explicit restrictions; it does not determine whether remote work is personally desirable.

Salary evidence qualityMedium confidence · Broad but usable range

The salary is source-provided and normalizable, but the advertised range is broad enough to reduce comparison precision.

Listing freshnessPosted today

The source posting date is today.

Source provenance evidenceEstablished source evidence

At least one enabled source recently observed the vacancy. The source chain is traceable, but this is not independent employer verification.

There is no universal opportunity score because pay, flexibility and access matter differently to different people. Compare Jobs lets you weight the evidence around your own priorities.

Decision checklist

What is supported, uncertain or worth checking?

This checklist separates supported strengths, visible cautions and missing evidence. It is not an overall recommendation or guarantee that the job is suitable for you.

Supported strengths

  • The available work-location evidence indicates strong location flexibility.

Visible cautions

  • At least about 10 years of experience required

Still unknown

  • Visa sponsorship is not established by the available listing data.

Qualifications & access

What qualifications are explicitly stated?

Some explicit entry barriers stated

EducationEducation requirement not established
Required experience evidenceAt least about 10 years of experience required
Explicit required barriers1
Explicit access signals0

Explicit requirements worth checking

  • At least about 10 years of experience required: The available wording contains an explicit minimum/required years-of-experience signal. Preferred years are tracked separately and never promoted into the required minimum.

Qualification signals come from explicit listing wording. Anything not mentioned remains unknown, so silence is never treated as proof that a degree, experience, licence or other requirement is unnecessary.

Pay vs. barriers

Pay and barrier context available

The current pay position can be viewed alongside the stated barriers, but the available detail does not support a stronger conclusion.

Current-sample pay position

Comparable disclosed-pay evidence places this job at about 36 / 100 within its current occupation/seniority sample.

Explicit stated barriers

1 explicit required barrier is visible in the available wording.

Required experience evidence

The listing states at least about 10 years of required experience.

Evidence gaps that could change this interpretation
  • Education requirement is not established.

This section weighs pay context against clearly stated barriers without collapsing unlike requirements into one universal score. Degree, experience, licensing, clearance and location limits remain separate, and missing qualification details stay unknown.

Beyond the headline

Not enough evidence for a hidden-value finding

Potential hidden value appears only when several distinct non-pay advantages are actually supported. Missing requirements or benefits are never counted as positives.

Strong location flexibility

The observable Remote Freedom evidence is strong and contains few explicit restriction signals.

Still check: At least about 10 years of experience required · The current application path is provider-mediated rather than directly classified as an employer-authorized or official route.

Hidden Value is an experimental evidence summary, not an investment-style score or guarantee of employability. It only uses explicit current listing evidence and does not infer that an unmentioned qualification is unnecessary.

Explainable opportunity highlight

Why this opportunity stands out

These are supported signals from the current listing and comparison sample—not a guarantee that this is the best job for you.

Strong remote flexibility

The observable work-location signals indicate unusually strong location flexibility.

Fresh opportunity

The source posting date is today.

Compensation intelligence

How competitive is this pay?

36/100

Below many comparable disclosed salaries

36%
Comparison familyData & AI roles · Senior / lead
Comparable salaries94
Current-sample medianUSD 178,500
Middle 50% of sampleUSD 130,250–222,616
Position in sampleAt or above about 36%
Comparison geographySame occupation, currency and seniority
Pay positionBelow the current median

The annualized midpoint is below the current comparable median but remains within the sample’s lower-to-middle range.

Why this analysis?

  • This score reflects the current advertised-pay distribution for comparable active jobs in the same currency. It measures pay position, not overall job quality.
  • Salary confidence: Medium. The salary is source-provided and normalizable, but the advertised range is broad enough to reduce comparison precision.
  • Range quality: Broad but usable range.

Employer compensation communication

Pay transparency at Leidos

Very strong current pay transparency

This score uses the employer’s current visible listings and combines how often pay is disclosed with how useful those ranges are. Bonus, equity and benefit mentions are shown separately and do not raise the score.

92/100
92%
Salary disclosure100% · 6 of 6 sampled listings
Range qualityMixed range quality
Bonus wording0 current listings
Equity wording6 current listings
Benefits wording1 current listings
Evidence strengthModerate

This pattern comes from the employer’s current visible vacancies. It describes hiring and pay transparency in those listings, not employee satisfaction or a permanent judgement of the employer.

Current employer intelligence

Leidos — current opportunity snapshot

Current opportunities visible6
Salary disclosure100%
Remote-policy evidence coverage100% · 6 of 6 sampled listings
Remote share of known arrangements100%
Worldwide-remote share100%
Known hiring countries0
Sponsorship evidence coverage0% · 0 of 6 sampled listings
Explicit sponsorship outcomes0 confirmed · 0 possible · 0 unavailable
Pattern sample6 of 6 · 100% coverage
Current role-family breadth3
Stated closing-date coverage100%
Relocation evidence coverage0% · 0 explicitly offered
Posted within 7 days33% of listings with a known posting date

Employer Evidence Profile

How often this employer’s current visible sampled vacancies state decision-critical information. These percentages describe evidence coverage, not employer quality.

Compensation100% of sampled current listings

Current sampled listings with advertised compensation evidence.

Work arrangement100% of sampled current listings

Current sampled listings whose work arrangement is clearer than unknown.

Location0% of sampled current listings

Current sampled listings with a supported country signal.

Application timing100% of sampled current listings

Current sampled listings with an explicit closing time.

Posting date100% of sampled current listings

Current sampled listings with a usable posting date.

Sponsorship0% of sampled current listings

Current sampled listings that explicitly indicate confirmed, possible or unavailable sponsorship evidence.

Relocation0% of sampled current listings

Current sampled listings with an explicit relocation signal.

Low coverage means the current visible listings state the information less often. It does not prove that the employer lacks the policy, benefit or support.

Common current occupation families: Operations (2) · Data & AI (1) · Healthcare (1)

Visible seniority mix: Senior / lead (6)

Current employment-type mix: Full time (6)

Other current roles from this employer

These are other current vacancies visible from the same employer, not endorsements or evidence of future hiring plans.

Current disclosed salary medians by currency

  • USD 140,525 median · 6 disclosed salaries

Questions worth asking this employer

  • If work authorization matters to you, what sponsorship policy applies to this specific role and location?
  • If a move is required, is relocation assistance available for this position?

These questions are prompted by missing or thin evidence in the employer’s current visible vacancies. Missing evidence is not treated as a negative judgement.

This employer snapshot uses the employer’s current visible listings. Remote and sponsorship rates use only vacancies with explicit evidence, while missing information stays unknown. Salary medians are shown separately by currency and need at least five disclosed salaries. Zero confirmed sponsorship means none was explicitly found in this sample, not that sponsorship is unavailable.

This snapshot describes the employer’s current visible vacancies—things such as pay disclosure and work arrangement. It is not an employee-satisfaction or hiring-quality rating, and different currencies stay separate.

Work-location intelligence

Remote Freedom

96/100

Highly location-flexible

96%

Why this score?

  • The source describes the role as open worldwide or globally.

Flexibility signals detected

  • Worldwide or global remote eligibility is explicitly indicated.

Remote Freedom measures observable location flexibility only. Unknown work-location information remains unscored. Timezone wording is penalized only when it appears restrictive; general collaboration across time zones is not treated as a restriction. A score does not guarantee legal work eligibility, payroll availability or visa sponsorship.

International applicant intelligence

Visa & relocation signals

Sponsorship status is shown only when the listing provides clear enough wording. Employer history or headquarters location is not used to guess an answer.

Visa sponsorshipSponsorship not established

The available listing details do not contain a clear enough sponsorship statement.

RelocationRelocation support not established

The available listing details do not contain a clear enough relocation statement.

Tradeoff check

What’s the catch?

No obvious trade-off appears in the available job details. That does not mean the role has no drawbacks, so the original listing and employment terms are still worth reading carefully.

Current alternatives

Better-paying alternatives

These current roles show a materially higher annualized salary midpoint in the same broad occupation and currency. Similar seniority, country, work arrangement, employment type and recency are preferred where possible; higher pay alone does not make an alternative a better fit.

Alternatives are drawn from the current inventory rather than presented as application recommendations. A pay difference needs to be meaningful—about 3% or more at the midpoint—and different currencies are not compared.

Application-path intelligence

What can we see about the application process?

Provider-mediated application path

The current application path comes through a publisher or aggregator. The destination may still lead to an employer-authorized hiring system, but that is not clear enough to assume.

Current destination: himalayas.app · HTTPS

No additional required application step is clear in the available listing text. This does not mean the external application is one-click or friction-free.

Application effort is estimated from visible listing and source details. Optional steps are kept separate from mandatory ones, and the external form may contain additional requirements that are not visible here.

Application safety context

Application safety check

Basic application-safety context available

The current application destination has a basic transport-safety signal such as HTTPS. This does not verify the employer, vacancy, recruiter or application process.

Evidence checked: Source provenance · Application destination · Listing wording

Observable transport-safety signals

  • The available application destination uses HTTPS.
Before you share money or sensitive information
  • Confirm the vacancy on the employer’s official careers site when practical, especially if a recruiter contacts you outside the listed application path.
  • Check that recruiter email domains and application destinations are consistent with the employer or an identifiable recruiting provider.
  • Do not pay application, processing, training or equipment fees merely to be considered for a job.
  • Do not send cryptocurrency, gift cards, online-banking credentials or PINs as part of an application.
  • Treat unusually fast offers or interviews conducted only through informal messaging channels as reasons to verify the employer independently.

This is a limited safety screen, not employer verification and not a fraud determination. Never send money, cryptocurrency, passwords or sensitive banking credentials merely because a listing appears on a job platform.

Original listing details

The section below comes from the listing source. The decision sections above use the job’s structured pay, location, qualification, mobility and application details to give you additional context.

**This position is contingent upon contract award.**


Leidos is seeking a Senior Data Engineer to support the Department of Veterans Affairs (VA) Summit Advanced Tooling, Lakehouse, and Artificial Intelligence Services (ATLAS) program.

Remote work within CONUS is subject to VA security and system-access requirements. Must support Eastern Time collaboration and applicable production coverage. Occasional after-hours or weekend support may be required for critical outages or planned maintenance.

This role focuses on engineering reusable ingestion, transformation, quality, and automation capabilities that improve the scalability, reliability, and efficiency of the Summit Data Platform across customer workgroups.

Primary Responsibilities

  • Design and implement reusable data ingestion, transformation, orchestration, and validation frameworks aligned with the Summit product roadmap and approved enterprise architecture.
  • Lead engineering of shared pipeline templates, data-quality gates, lineage instrumentation, and automated deployment or recovery patterns that reduce manual effort across workgroups.
  • Optimize cloud data processing, partitioning, performance, reliability, and cost; establish practical technical measures and tuning recommendations.
  • Provide technical guidance on complex data integration, source parity, semantic modeling, and federated query capabilities; collaborate with architecture and governance leads.
  • Integrate automated testing, observability, CI/CD, infrastructure-as-code where appropriate, and secure access controls into production data engineering workflows.
  • Troubleshoot complex cross-platform failures and data-quality issues; coordinate root-cause analysis, remediation, rollback, and operational readiness.
  • Maintain reusable design documentation, standards implementation guidance, runbooks, and technical decision records.
  • Mentor engineers and coordinate with customer-requested engineering teams to promote adoption and reuse of common capabilities.

Required Qualifications

  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline and 10+ years of relevant experience, including demonstrated expertise designing and implementing complex data engineering solutions.
  • Hands-on experience developing and troubleshooting production data ingestion, ETL/ELT, transformation, and validation pipelines using SQL and Python.
  • Experience with cloud-based data platforms and services in Microsoft Azure, AWS, or Google Cloud; understanding of storage, orchestration, and secure data access.
  • Experience with data modeling, source-to-target reconciliation, data quality testing, and pipeline monitoring or incident troubleshooting.
  • Ability to document technical designs, data flows, dependencies, and operational procedures and collaborate with engineers, analysts, and data owners.
  • Demonstrated experience designing reusable production data engineering frameworks or shared services and independently resolving complex integration and performance issues.
  • Experience improving data engineering delivery through automation, testing, CI/CD, or standardized deployment patterns.
  • Ability to obtain and maintain the required VA Public Trust suitability determination (Tier 2/Moderate Risk).

Preferred Qualifications

  • Highly Preferred: Direct, hands-on experience supporting the VA Summit Data Platform is highly preferred; experience with other VA enterprise data and analytics environments is also valuable.
  • Experience with production-scale Spark/Databricks or Delta Lake processing and platform-wide performance or cost optimization.
  • Experience mentoring engineers or coordinating shared engineering capabilities across multiple delivery teams.
  • Hands-on Microsoft Azure data engineering experience, including Azure Data Factory, Azure Data Lake Storage, Azure Databricks, Spark, or comparable services.
  • Familiarity with Delta Lake/lakehouse architectures, data catalogs and lineage, and governance tools such as Collibra, Immuta, or Starburst.
  • Experience supporting federal IT systems and complying with security, privacy, and data-access requirements.
  • Experience with Agile delivery and relevant cloud/data engineering certifications. such as Microsoft Certified: Azure Data Engineer Associate, Databricks Certified Data Engineer Professional, AWS Certified Data Engineer – Associate, or equivalent.

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

Original Posting:

November 6, 2026

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

Pay Range $107,900.00 - $195,050.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

Originally posted on Himalayas

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