Job intelligence
Senior Data Engineer (remote from Portugal or selected EU countries)
FCamara
Before relying on the listing: Confirm Compensation with the employer or source. See verification questions
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.
Fast read
Opportunity DNA
The strongest upside: location flexibility looks unusually broad. The main trade-off: the pay picture is incomplete.
A financial comparison will need the approved compensation range.
No material geography, office-attendance or timezone restriction is visible in the available wording.
One or more material qualification requirements are stated and may narrow the realistic applicant pool.
Sponsorship and relocation support are not clear from the current listing.
Part of the application route can be assessed, but the full external process may contain additional steps.
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
4 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
- Work arrangement
- Advertised location
- Application closing time
- Employment type
What to verify next
- Compensation: What is the approved compensation range, and what portion is guaranteed base pay rather than variable compensation?
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 pay picture is incomplete: No usable salary range is stated, so a meaningful financial comparison is not possible yet.
- The experience requirement raises the entry bar: The listing appears to require at least about 6 years of experience.
Questions worth asking before you invest more time
- Ask for the approved compensation range before comparing this opportunity financially.
- 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.
Sr Data and AI Engineer
Abstra · Remote — Worldwide
Why it is nearby: Same seniority band · Similar work arrangement · Same employment type
FDE Data Engineer- Space (FedD141/FedD147)
Defense Unicorns · USA
Why it is nearby: Same seniority band · Similar work arrangement · Recently posted
Senior AI Engineer
Blue Orange Digital · Remote — Worldwide
Why it is nearby: Same seniority band · Similar work arrangement · Recently posted
Senior Data Engineer - Data Infra (Ontario, Canada)
Dandy · Canada
Why it is nearby: Same seniority band · Similar work arrangement · Recently posted
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.
200 most recent current roles sampled for the disclosure measures below.
Distinct employers in the bounded current sample, not an estimate of all employers hiring in the market.
Current sampled roles stating at least four of the five Core Decision Facts.
Requires a numeric amount, explicit ISO currency and supported pay period.
Listings with explicit enough remote, hybrid or on-site evidence to classify.
Missing deadline evidence remains unknown and is not interpreted as an open-ended application window.
Currencies with explicit pay evidence in the sample: USD (42) · EUR (17) · GBP (5) · CAD (2). 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.
Counts only affirmative or possible sponsorship evidence, or relocation explicitly offered. Unknown is not treated as no.
Uses only roles with a stated employment type.
A much stricter subset: only listings with explicit worldwide-remote evidence remain.
Shows the subset with enough stated evidence for a more informed first comparison.
Requires amount, explicit ISO currency and a supported pay period. Missing pay evidence remains unknown.
Counts roles explicitly classified as worldwide remote, region-restricted remote or remote with restrictions still unclear.
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 1188 visible roles in this broad family.
Salary transparency context
Is pay disclosure typical for this kind of role?
This listing does not state usable structured compensation. About 34% of the bounded current role sample does.
Compensation counts only when amount, ISO currency and supported pay period are all known.
Pay disclosure is limited in the current role sample.
This employer’s current visible listings disclose pay materially less 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.
Negotiation evidence available: 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.
The approved base-pay range is not established in the listing.
Variable compensation is mentioned; verify amount, formula, target and eligibility.
Equity or long-term incentive language is mentioned; verify grant type, vesting and valuation basis.
Retirement or pension benefits are mentioned; verify employer contribution and vesting.
Health-benefit language is mentioned; verify coverage, dependants and employee cost.
Paid-leave language is mentioned; verify the exact entitlement and carry-over rules.
A work-arrangement signal is available; verify schedule details before relying on it.
Relocation support not established
Sponsorship not established
A review cycle is mentioned; verify timing and whether compensation can change at that review.
Questions worth taking into the offer conversation
- What is the approved base-pay range for this role?
- Is there a bonus, commission or other variable-pay component, and how is it calculated?
- Does the package include equity or another long-term incentive, and what are the vesting terms?
- 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?
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.
European occupation references
This service uses the ESCO classification of the European Commission.
U.S. occupation references
- Data Scientists 15-2051.00
- Computer and Information Research Scientists 15-1221.00
- Social Science Research Assistants 19-4061.00
- Atmospheric and Space Scientists 19-2021.00
- Bioinformatics Scientists 19-1029.01
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
- statistical modeling techniques
- perform project management
- query languages
- online analytical processing
- develop data processing applications
- data engineeringPhrase in listing
- manage data collection systems
Context-dependent ESCO skills
- manage ICT data architecture
- SPARQL
- use spreadsheets software
- computational biology
- state estimation
O*NET · U.S. occupation
Data Scientists
O*NET occupation skills
- Mathematics
- Critical ThinkingPhrase in listing
- 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.
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
Banco de Talentos | Desenvolvedor Fullstack Sênior (Node/React)
FCamara · Remote — Worldwide
same seniority band · similar work-arrangement evidenceSenior Software Engineer - Integrations
Dropzone AI · Remote — Worldwide
same seniority band · similar work-arrangement evidenceIS Manager - Developer Experience (DevEx)
Mutual Of Omaha · Remote — Worldwide
same seniority band · similar work-arrangement evidenceAdjacent-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
AI Data Analyst - Merchant Acquisition
Paynada · Remote — Worldwide
Similar work arrangement · Recently postedData Engineer
MicroSourcing · Remote — Worldwide
Similar work arrangement · Recently postedStretch direction
Analytics Engineer
Alma · France
Similar work arrangement · Recently postedSr. Director of Machine Learning
hims & hers · USA
Similar work arrangement · Recently postedThese 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?
Azure is one of the signals this listing shares with skills appearing often across current Data & AI roles opportunities.
Skills named in this listing
Shared with the current career sample
- Azure Seen in 16 sampled listings
- Databricks Seen in 19 sampled listings
- Generative AI Seen in 11 sampled listings
- Python Seen in 87 sampled listings
Combinations also appearing together
- Python + SQL appeared together in 61 sampled listings
Additional signals in this listing: Terraform
Application edge
- If these skills match your background, prepare one concrete example that shows how you used Azure, Databricks, and Generative AI rather than relying on a keyword-only claim.
- The listing states about 6 years of required experience. Check that the dates and scope in your application make that experience easy to verify.
- The listing mentions extra application steps. Review those requirements before starting so you can prepare the requested material in one pass.
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; 115 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.
At least about 6 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.
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.
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.
Generative AI
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.
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.
SQL
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.
Terraform
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.
Prepare for a stated application step
An assessment, test or work-sample step is explicitly mentioned.
Questions worth resolving before you rely on the opportunity
- Compensation: What is the approved compensation range, and what portion is guaranteed base pay rather than variable compensation?
- Work authorization / sponsorship: If sponsorship or work authorization matters to you, what exact immigration or employer-sponsorship conditions apply to this role?
Decision analysis
What the listing really tells you
The headline alone does not tell the whole story for Senior Data Engineer (remote from Portugal or selected EU countries) at FCamara. The clearest decision context comes from the location rules are clear enough to judge, the listing gives useful clues about who can realistically enter, and the application route gives a few useful clues.
The location rules are clear enough to judge
Location flexibility can be assessed here: Highly location-flexible, with a Remote Freedom reading of 96/100.
The listing gives useful clues about who can realistically enter
At least about 6 years of experience required · 1 additional stated barrier. Only requirements actually stated in the listing are counted; anything left unsaid remains unresolved.
The application route gives a few useful clues
Provider-mediated application path · 1 visible process step. The external application may contain additional steps that are not visible from the listing itself.
The listing can be traced to a current source
The opportunity currently has 1 renewable source path across 1 source classes. Multiple independent paths can strengthen continuity, but they are not a substitute for checking the application destination.
How this analysis is assembled
The brief pulls together the parts of the vacancy that can be compared reliably today. Gaps in the listing remain visible instead of being filled with assumptions.
Analysis evidence coverage
How much analysis can the current evidence support?
Comparable salary data is not available for this job yet.
Measures observable location flexibility and explicit restrictions; it does not determine whether remote work is personally desirable.
Missing compensation is not treated as negative evidence; this dimension simply remains unavailable.
The source posting date is today.
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
- The listing appears to require substantial prior experience.
- This is not a standard permanent full-time arrangement; compare benefits, taxes and continuity as well as headline pay.
- At least about 6 years of experience required
Still unknown
- There is not enough comparable salary evidence to establish this job’s current pay position.
- Visa sponsorship is not established by the available listing data.
Pay vs. barriers
Opportunity Efficiency not assessed
The current pay position is not reliable enough to weigh compensation against the stated barriers.
1 explicit required barrier is visible in the available wording.
The listing states at least about 6 years of required experience.
- Current comparable pay position is unavailable.
- 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.
The observable Remote Freedom evidence is strong and contains few explicit restriction signals.
Still check: At least about 6 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.
The observable work-location signals indicate unusually strong location flexibility.
The source posting date is today.
Compensation intelligence
How competitive is this pay?
Comparable salary data is not available for this job yet.
Why this analysis?
- Comparable salary data is not available for this job yet.
- Salary confidence: Not available. No disclosed salary can currently be normalized for comparison. Missing compensation is not treated as low-quality salary evidence.
- Range quality: No disclosed range.
Employer compensation communication
Pay transparency at FCamara
Limited 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.
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
FCamara — current opportunity snapshot
Employer Evidence Profile
How often this employer’s current visible sampled vacancies state decision-critical information. These percentages describe evidence coverage, not employer quality.
Current sampled listings with advertised compensation evidence.
Current sampled listings whose work arrangement is clearer than unknown.
Current sampled listings with a supported country signal.
Current sampled listings with an explicit closing time.
Current sampled listings with a usable posting date.
Current sampled listings that explicitly indicate confirmed, possible or unavailable sponsorship evidence.
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: Data & AI (1) · Software engineering (1) · Design (1)
Visible seniority mix: Mid-career (1) · Senior / lead (2)
Current employment-type mix: Full time (2) · Contract (1)
Other current roles from this employer
Banco de Talentos | Desenvolvedor Fullstack Sênior (Node/React)
Remote — Worldwide
Senior / lead · Worldwide remoteUX/UI Designer - Pleno
Remote — Worldwide
Mid-career · Worldwide remoteThese are other current vacancies visible from the same employer, not endorsements or evidence of future hiring plans.
There are not yet five current disclosed salaries in one currency, so an employer pay median would be too thin to be useful.
Questions worth asking this employer
- What compensation range applies to this role, and which parts of total compensation are fixed versus variable?
- 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
Highly location-flexible
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.
The available listing details do not contain a clear enough sponsorship statement.
The available listing details do not contain a clear enough relocation statement.
Tradeoff check
What’s the catch?
These are visible conditions worth checking before treating the headline compensation as the whole story:
- The listing appears to require substantial prior experience.
- This is not a standard permanent full-time arrangement; compare benefits, taxes and continuity as well as headline pay.
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
Visible application steps or requirements
- An assessment, test or work-sample step is explicitly mentioned.
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.
We are looking for Senior Data Engineer with strong English skills to join us in a project with a Europe-based company. This is a remote position, and we will consider candidates from Portugal and a limited set of EU countries.
Our Client is a global player in the field of operations, risk, and sustainability services and solutions for companies and industries across the world. As they provide both services and technology for their clients, the Senior Data Engineer we are looking for will support the delivery of value across client's operations and technology ecosystem.
In this position, you are hired by FCamara Europe, the European division of one of the largest and fast-growing tech and cognitive services group in Brazil, with +1500 specialists and engineers. From Portugal we deliver services to the EU, UK, US and MENA, bringing together multicultural, diverse and creative teams through projects, managed services, squads, and staff augmentation.
In this role, you will be primarily responsible for acting as the technical reference for our Client’s Databricks data platform, designing and operating reliable data pipelines, implementing DataOps and CI/CD practices, and establishing strong data governance to ensure secure, traceable, and AI-ready datasets.
In a typical week you will:
- Design, build, and optimise batch and streaming data pipelines on Databricks using PySpark, Spark SQL, Delta Lake, and Delta Live Tables.
- Evolve the Lakehouse architecture (bronze, silver, and gold layers) to ingest and transform operational, behavioural, and HSE data from multiple clients and sources.
- Implement and maintain CI/CD pipelines for data workloads using Databricks Asset Bundles, Git, Azure DevOps, or GitHub Actions.
- Automate data testing, quality checks, and promotion across development, staging, and production environments.
- Implement and manage Unity Catalog, including catalogs, permissions, lineage, auditing, and data access policies.
- Define and enforce data governance standards, security controls, data masking, and per-client data isolation to ensure compliance with LGPD and GDPR.
- Monitor pipeline performance, define SLAs, set up alerts, and lead incident reviews.
- Provision infrastructure as code using Terraform and standardise pipeline templates and best practices.
- Act as a technical reference by reviewing code, mentoring mid-level and junior engineers, and collaborating with product, data science, and consulting teams.
- Document architecture decisions, technical standards, and data engineering best practices.
Seniority: Due to the nature of the position, we are looking for someone with at least 6+ years of experience in similar roles, including 3+ years working with Databricks in production environments.
To be considered for the role, it is mandatory you to fulfill these requirements:
- Strong hands-on experience with Databricks in production, including PySpark, Spark SQL, Delta Lake, and Delta Live Tables / Lakeflow.
- Solid experience designing and optimising batch and streaming pipelines and evolving Lakehouse architectures (bronze, silver, gold layers).
- Proven experience implementing CI/CD for data workloads using Git, Azure DevOps or GitHub Actions, and Databricks Asset Bundles.
- Practical DataOps experience, including automated testing, pipeline versioning, observability, and monitoring.
- Hands-on experience with data governance, ideally using Unity Catalog (access control, lineage, and auditing).
- Experience with Infrastructure as Code using Terraform.
- Strong proficiency in Python, PySpark, and advanced SQL.
- Cloud experience, preferably on Azure (ADLS, Data Factory, Key Vault, Entra ID).
- Experience with agentic coding.
- Fluent English to work with global teams and clients.
It will be very well appreciated if you also bring:
- Databricks Data Engineer Professional certification or Azure certifications (DP-203 / DP-700).
- Experience with multi-tenant SaaS platforms and per-client data isolation.
- Knowledge of MLOps practices (MLflow, Feature Store, Model Serving) and building data pipelines for generative AI / RAG.
- Experience with Microsoft Purview.
- Experience with data quality tools (Great Expectations, Lakehouse Monitoring, dbt).
- Experience with streaming technologies (Kafka, Event Hubs, or Structured Streaming).
- Domain knowledge in HSE, industrial operations, or risk management data.
Beyond technical knowledge, we also expect you to have a collaborative and team-oriented profile:
- Ability to understand requirements and technical solutions
- Strong communication skills
- Critical thinking and a focus on continuous improvement
- Strong delivery mindset and commitment to deadlines and goals
Informações adicionais
This is a fully remote position. You may occasionally be invited or requested to visit Client or FCamara sites in Portugal or Central Europe on an occasional, pre-planned basis. Regular office visits are not anticipated.
Accepted Countries: Please note that due to contractual and compliance requirements, this role is currently limited to individuals currently and lawfully residing with a work permit in the following countries: Portugal, Bulgaria, Croatia, Estonia, Hungary, Latvia, Lithuania, Slovakia, and Romania.
Nationality and Visa Sponsorship: We welcome you, regardless of your nationality, provided you meet the role requirements and are legally resident in one of the accepted countries. Please note that we do not provide visa sponsorship or relocation support for this role.
This role requires English at a minimum B2+ level (professional working proficiency): Please note that English is the primary language used in the project, and a minimum B2 level is required. If English is not your primary language, we may ask you to complete a fluency assessment.
Long-term project: This position is part of a long-term project.
Contract Model: The role may be offered under one of the following arrangements, depending on your location, interests and professional profile: employment contract, independent contractor, or B2B.
Originally posted on Himalayas
Listing provenance
Where did this job come from?
See where this vacancy came from and whether more than one current source can still support it. Source names help with traceability and attribution; they are not endorsements or guarantees.
At least one enabled source recently observed the vacancy. The source chain is traceable, but this is not independent employer verification.
- Continuity
- One recent renewable source
- Source-class independence
- One renewable source class
- Last source observation
- Observed very recently
This records when High Paid Job last observed the vacancy in source evidence. It confirms source presence, not that the employer edited the vacancy at that time.
- 1 enabled source recently observed this vacancy.
Source confidence is about traceability and continuity. It is separate from application safety and should not be read as an employer reputation rating.
The vacancy is supplied by an external job publisher. Source information helps show where the listing came from; it is not a guarantee about the employer or vacancy.
Listing source: Himalayas. Destination: himalayas.app. The application opens in a new tab so you can keep this report open.