Data Governance Engineer

Fractal; United States; On-site; USD 100,000 - 120,000; Full time

Benefits offered by this job

Health insurance

401(k) Plan

Paid holidays

Parental Leave

Flexible PTO

Job summary

A strategic AI partner based in the United States is looking for a Data Foundations & Lineage Engineer to build and maintain the core data ecosystem for Learning Data Intelligence. This role involves defining datasets' structure and ensuring they are discoverable and trustworthy. Candidates should have 4+ years of experience in data engineering, strong SQL skills, and familiarity with Azure Data Lake and Databricks. The position offers a competitive salary range of $100,000 to $120,000 per year and comprehensive benefits including health insurance and paid parental leave.

Qualifications

• 4+ years in data engineering, data analysis, data governance, or related fields.
• Strong SQL and data profiling skills; ability to reverse‑engineer unknown datasets.
• Familiarity with metadata systems, data cataloging, and lineage tools.

Responsibilities

• Build, document, and maintain the core data ecosystem for Learning Data Intelligence.
• Develop end‑to‑end lineage for Learning datasets.
• Work closely with analytics, engineering, content, and program teams.

Skills

SQL

Data profiling

Data governance

Data analysis

Tools

Azure Data Lake

Databricks

Power BI

Synapse

Job description

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Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets; an ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.

Please visit Fractal | Intelligence for Imagination for more information about Fractal.

We are looking for a Data Foundations & Lineage Engineer who will build, document, and maintain the core data ecosystem that powers Learning Data Intelligence. This role will be responsible for defining the structure, lineage, quality, and meaning of datasets in the Learning Lake (e.g., HCM, Finance, HRDP, FDL), and ensuring every dataset is discoverable, well‑documented, and trustworthy.

You will work hands‑on across the Lakehouse, mapping schemas, tracing lineage, profiling quality, eliminating manual dependencies, and building a durable documentation layer that serves engineering, analytics, AI agents, and business stakeholders. This work is foundational to our FY26/FY27 Data Intelligence Strategy pillars of Data Foundation & Technology and Data Quality & Governance.

Data Discovery & Documentation

• Perform deep, brute‑force exploration of all Learning Lake schemas and tables to understand their meaning, business purpose, and dependencies.
• Build a comprehensive documentation repository describing dataset definitions, column‑level semantics, business logic, refresh cadences, source systems, and downstream consumption patterns.
• Translate implicit, tribal‑knowledge data flows into explicit, searchable documentation consistent with guidance.
• Develop end‑to‑end lineage for Learning datasets, mapping sources, transformations, pipelines, and consumption (Power BI, semantic models, AI agents, etc.).
• Identify and eliminate manual or undocumented data feeds, aligning with the Manual Dependency Elimination initiative.

Collaboration & Stakeholder Alignment

• Work closely with the DRI team as subject‑matter partners; elevate questions and validate assumptions.
• Partner with analytics, engineering, content, and program teams to ensure data design supports downstream reporting, modeling, and AI use cases.
• Build the foundational metadata that powers data discovery, semantic models, and self‑service analytics.
• Produce guides, readme files, and onboarding materials for all teams relying on Learning Lake.

Required Qualifications

• 4+ years in data engineering, data analysis, data governance, or related fields.
• Strong SQL and data profiling skills; ability to reverse‑engineer unknown datasets.
• Experience with Azure Data Lake, Fabric, Databricks, Synapse.
• Familiarity with metadata systems, data cataloging, and lineage tools.
• Ability to navigate ambiguous, undocumented data environments.

Compensation

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is: $100,000 to $120,000 Yearly. In addition, you may be eligible for a discretionary bonus for the current performance period.

Benefits

As a full‑time employee of the company or as an hourly employee working more than 30 hours per week, you will be eligible to participate in the health, dental, vision, life insurance, and disability plans in accordance with the plan documents, which may be amended from time to time. You will be eligible for benefits on the first day of employment with the Company. In addition, you are eligible to participate in the Company 401(k) Plan after 30 days of employment, in accordance with the applicable plan terms. The Company provides 11 paid holidays and 12 weeks of Parental Leave. We also follow a “free time” PTO policy, allowing you the flexibility to take the time needed for either sick time or vacation.

Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.