Job intelligence
Senior Data Engineer
Worldly
Before relying on the listing: Confirm Application closing time 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 available details do not point to a single standout advantage yet. The clearest issue to weigh is location rules could change the fit.
Current comparable position is around the 23th percentile.
Geographic eligibility is restricted to a country or region.
The listing does not make the minimum education or experience threshold clear enough yet.
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
- Compensation
- Work arrangement
- Advertised location
- Employment type
What to verify next
- Application closing time: Is there a firm application deadline, a rolling review window or no stated closing date?
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
Nothing stands out strongly enough yet to call a clear advantage. The role may still be attractive for reasons the listing does not spell out.
Trade-offs to weigh
- Location rules could change the fit: Geographic eligibility is restricted to a country or region.
Questions worth asking before you invest more time
- Confirm whether a degree is actually required, preferred, or replaceable with equivalent experience.
- Confirm the actual minimum experience requirement rather than assuming preferred background is mandatory.
- 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.
Principal Data Scientist, User Ecosystem
Reddit · USA
Why it is nearby: Same seniority band · Same country · Similar work arrangement
About 126% higher advertised midpoint
Engineering Manager, Machine Learning (Safety)
Discord · USA
Why it is nearby: Same seniority band · Same country · Similar work arrangement
About 104% higher advertised midpoint
Senior AI Engineer, Voice Platform
ClickUp · USA
Why it is nearby: Same seniority band · Same country · Similar work arrangement
About 50% higher advertised midpoint
Data Scientist, Corporate
YipitData · USA
Why it is nearby: Same seniority band · Same country · Similar work arrangement
About 13% 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.
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 (50) · EUR (6) · GBP (4) · CHF (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.
Counts only affirmative or possible sponsorship evidence, or relocation explicitly offered. Unknown is not treated as no.
A much stricter subset: only listings with explicit worldwide-remote evidence remain.
Counts roles explicitly classified as worldwide remote, region-restricted remote or remote with restrictions still unclear.
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.
Uses only roles where a country is known. Roles without country evidence are excluded from this denominator.
Only same-currency opportunities with usable annualized pay enter this comparison. Other currencies are not converted or treated as lower.
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 1245 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 30% of the bounded current role sample does the same.
Compensation counts only when amount, ISO currency and supported pay period are all known.
Pay disclosure is limited in the current role sample.
Employer-level comparison is withheld until enough current employer listings are available.
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: 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.
Usable advertised compensation is available.
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
- Is there a bonus, commission or other variable-pay component, and how is it calculated?
- 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?
- Is there a firm application deadline, a rolling review window or no stated closing date?
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
- 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.
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
Sr. Counsel; Product, Privacy, and AI
Veeam Software · USA
same stated country · same seniority band · same employment typeSenior Staff Platform Engineer
Veeam Software · USA
same stated country · same seniority band · same employment typeSenior Fullstack Engineer, FanX AI
SeatGeek · USA
same stated country · same seniority band · same employment typeAdjacent-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
FBS Associate Data Engineer
Capgemini Technology Services · Remote — Worldwide
Similar work arrangement · Same employment type · Recently postedData Engineer & PowerBI Developer
LUZA Group · Remote — Worldwide
Similar work arrangement · Same employment type · Recently postedStretch direction
Staff Data Analyst, Marketing
1Password · Canada, USA
Same country · Similar work arrangement · Same employment type Advertised midpoint is about 22% higherStaff Data Scientist
hims & hers · USA
Same country · Similar work arrangement · Same employment type Advertised midpoint is about 40% higherThese 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
Shared with the current career sample
- AWS Seen in 36 sampled listings
- Large Language Models Seen in 38 sampled listings
- Python Seen in 82 sampled listings
Combinations also appearing together
- Python + SQL appeared together in 63 sampled listings
- AWS + Python appeared together in 30 sampled listings
- Large Language Models + Python appeared together in 26 sampled listings
Additional signals in this listing: Agile · Docker · Generative AI · MongoDB
Application edge
- If these skills match your background, prepare one concrete example that shows how you used Agile, AWS, and Docker rather than relying on a keyword-only claim.
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; 118 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.
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.
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.
Docker
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.
Large Language Models
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.
MongoDB
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
- Application closing time: Is there a firm application deadline, a rolling review window or no stated closing date?
- 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
For Senior Data Engineer at Worldly, the most useful clues right now are compensation has enough depth for comparison, remote flexibility can be weighed properly, and the visible application effort can be estimated. Looking at them together makes the trade-offs easier to see.
Compensation has enough depth for comparison
The annualized midpoint sits near the 23th percentile within 60 comparable USD salary observations. Treat that as current advertised-pay context rather than a forecast of take-home or total compensation.
Remote flexibility can be weighed properly
The work-location pattern is “Limited location freedom”, with Remote Freedom at 54/100. One practical limit to notice is geographic eligibility is restricted to a country or region..
The visible application effort can be estimated
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
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?
Uses the explainable High Pay Score within the job’s current occupation/seniority/currency comparison sample.
Measures observable location flexibility and explicit restrictions; it does not determine whether remote work is personally desirable.
The configured source supplied structured salary fields, a usable currency and a focused comparison value.
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
No standout strength is supported strongly enough to list here. That is not a negative rating.
Visible cautions
- Geographic eligibility is restricted to a country or region.
- Work-related travel is required or expected.
- Some compensation may be variable or performance-based. Confirm the guaranteed base amount before comparing headline pay.
- The description appears to require or expect work-related travel. Check the frequency and whether travel time or expenses materially affect the role.
Still unknown
- Visa sponsorship is not established by the available listing data.
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.
Comparable disclosed-pay evidence places this job at about 23 / 100 within its current occupation/seniority sample.
2 explicit Remote Freedom restriction signals are present and are shown separately from qualification requirements.
- Education requirement is not established.
- Required prior-experience level 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.
Still check: 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 source provides structured salary information with a comparatively focused range, improving the usefulness of pay comparisons.
The source posting date is today.
Compensation intelligence
How competitive is this pay?
Below many comparable disclosed salaries
The annualized midpoint is below the 25th percentile boundary of the current comparable sample.
The highlighted band is the middle 50% of the current comparable sample after the outlier guard. The dark marker is this job’s annualized salary midpoint.
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: High. The configured source supplied structured salary fields, a usable currency and a focused comparison value.
- Range quality: Focused salary range.
Employer compensation communication
Pay transparency at Worldly
Only 1 current listing from this employer is indexed. At least three are required before employer-level pay transparency is summarized.
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
Worldly — current opportunity snapshot
Only 1 current listing from this employer is visible. At least three are needed before an employer pattern is shown.
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
Limited location freedom
Why this score?
- The role is remote but the source identifies a country or regional restriction.
Location restrictions detected
- Geographic eligibility is restricted to a country or region.
- Work-related travel is required or expected.
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:
- Some compensation may be variable or performance-based. Confirm the guaranteed base amount before comparing headline pay.
- The description appears to require or expect work-related travel. Check the frequency and whether travel time or expenses materially affect the role.
- This is remote work with a geographic restriction, not a worldwide-remote vacancy.
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.
Senior Staff Machine Learning Engineer - Content Platform
Spotify · USA
Region-restricted remoteWhy comparable: Same seniority band · Same country · Similar work-location arrangement
Principal Data Scientist, User Ecosystem
Reddit · USA
Region-restricted remoteWhy comparable: Same seniority band · Same country · Similar work-location arrangement
Engineering Manager, Machine Learning (Safety)
Discord · USA
Region-restricted remoteWhy comparable: Same seniority band · Same country · Similar work-location arrangement
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: jobicy.com · 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.
Senior Data Engineer
Location: Remote - US
About Worldly
Worldly is the world's most comprehensive impact intelligence platform — delivering real data to businesses on impacts within their supply chain. Worldly is trusted by 40,000 global brands, retailers, and manufacturers to provide the single source of ESG intelligence they need to accelerate business and industry transformation.
Through strategic and meaningful customer relationships, Worldly provides key insights into supplier performance, product impact, trends analysis, and compliance. When a company wants to change how business is done, we enable that systemic shift.
Backed by a dedicated global team of individuals aligned by values, Worldly proudly operates as a public benefit corporation with backing from mission-aligned investors. Want to learn more? Read our story.
About the Opportunity
Worldly is hiring a hands-on data engineer with a passion for sustainability to join our dynamic team. You will take on a primary role in building, operating, maintaining, and evolving the systems that support our internal analytics and power our customer-facing analytics platforms.
In this role, you will:
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Own our production data lake — a CDC-fed, medallion (bronze/silver/gold) lake on Apache Iceberg, queried through Trino — as well as our independent Postgres data warehouse.
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Play a core role in integrating our graph database with the warehouse, lake, and primary databases, including migrating legacy pipelines onto a single, governed integration layer.
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Apply generative AI and embeddings-based techniques already running in production (e.g., entity matching, document extraction) to keep expanding what our data can do.
What You'll Do
Data Warehouse & Data Lake
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Operate and evolve our Postgres data warehouse (schema, performance, access controls) and build analytics-ready datasets from it.
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Own the lake end-to-end: CDC ingestion (source database → message bus → streaming writer → Iceberg bronze/silver/gold), the Trino query layer, and the table catalog.
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Own pipeline health — latency SLAs, schema-drift detection, source reconciliation — and the GitOps/Terraform infrastructure and backup/DR posture underneath it.
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Bring consistent schemas, documented lineage, and clear ownership to a data estate that's grown quickly through acquisitions.
Orchestration, Transformation & Reporting
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Maintain and evolve our Dagster-orchestrated dbt pipelines: sensor-triggered and scheduled builds, data quality tests, branch-based versioning for curated releases.
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Operate our BI/reporting layer, including per-user, policy-based data access enforced at the query engine (not just the dashboard), and consistent metric definitions across dashboards.
Graph Integration
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Own pipelines integrating the graph database with the warehouse, lake, and primary databases, working within canonical data models and a single write path.
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Partner with data science to migrate legacy direct-to-graph services onto that shared path, and to evolve relational structures into graph-native models.
GenAI/NLP Enablement
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Support and extend production genAI workflows — embeddings/similarity search, LLM-based extraction and classification — and keep our data infrastructure "AI-ready."
We'd Like to See
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5+ years in data engineering, analytics engineering, or data platform engineering.
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Advanced SQL and relational database experience (Postgres, MongoDB).
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Hands-on graph database experience in production, including integrating graph models with warehouses and lakes — core, not peripheral, to this role.
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Experience with open table formats and medallion lake architectures (e.g., Apache Iceberg) and distributed SQL engines (e.g., Trino, Presto).
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Experience with streaming/CDC pipelines (e.g., Kafka or Pulsar, Debezium, Flink or similar).
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Strong Python skills for pipelines, automation, and operational tooling.
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Experience with dbt orchestrated by a modern scheduler (e.g., Dagster, Airflow).
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AWS infrastructure experience (EKS, VPC, IAM, S3) via infrastructure-as-code (e.g., Terraform), plus CI/CD, GitOps (e.g., ArgoCD), and Docker.
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Experience with analytics data modeling, metric definitions, and automated monitoring/data-quality controls.
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Experience operating production data systems: incident triage, root-cause analysis, runbooks, reliability improvements.
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Comfortable working with cross-functional/analytics stakeholders (Jira/Confluence, Agile).
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Familiarity with data security practices (PII protection, encryption, access management).
It Helps If You Have
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Experience with BI tooling supporting per-user, policy-based data access (e.g., Superset with SSO impersonation).
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Experience with policy-based access control (e.g., OPA) and identity platforms (e.g., Keycloak).
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Familiarity with multi-region data residency (e.g., separate EU/China data handling).
What We Can Offer You
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Medical, Dental, and Vision Insurance are offered through multiple PPO options. Worldly covers 90% of employee premiums and 60% of spouse/dependent premiums.
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Company-sponsored 401k with up to 4% match for US employees.
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Incentive Stock Options.
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100% Parental Paid Leave.
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Unlimited PTO.
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12 paid company holidays.
Life at Worldly
Our team is motivated to transform the way products are made. By helping our customers succeed in a new era of sustainable production, we can build technology that makes a difference on a planetary level.
Our team represents over 15 countries and brings unique experiences from technology to farming to the table. Surround yourself with kind, enthusiastic, and dedicated people who put collaboration and growth at the center of our shared goals.
Benefits and Perks
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Earn a competitive salary and performance-based bonuses. Get healthcare, retirement matching, and equity for US employees.
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Use the office stipend to get the supplies you need—combat Zoom fatigue with no-meeting Fridays.
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Flexible time off. Take the time you need to recharge. Our culture encourages team members to explore and rest to be their best selves.
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We're remote, not lonely. Join the culture committee, coffee chats, or a variety of other interest groups.
Travel Notice
Roles at Worldly may require occasional travel to support business needs, including but not limited to team collaboration, customer engagement, or company events.
Equity Statement
We believe reflecting the diversity of those we strive to serve is essential. True innovation happens when everyone has room at the table, including the tools, resources, and opportunity to excel. We're dedicated to building a culturally and experientially diverse team that leads and works with empathy and respect.
Compensation Overview
Annual Base Rate (USD): $135,000 - $165,000
10% Annual Bonus
Incentive Stock Option Package
Work-From-Home Stipends
*Final compensation figures will be determined based on a wide variety of factors, including experience and location. These factors will be evaluated and considered by Worldly throughout the entirety of this process.
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: Jobicy. Destination: jobicy.com. The application opens in a new tab so you can keep this report open.