Principal Lead- Product Data Engineer

About the company

Job description

Product and requirements

• Translate business outcomes into technically actionable, build-ready requirements.
• Decompose epics and features into engineering-backed user stories with acceptance criteria and technical context.
• Align product intent, architectural standards, and platform capabilities.

Technical collaboration

• Act as a technical conduit between product and engineering teams and clarify design trade-offs and constraints.
• Participate in solution discussions, architecture reviews, and technical refinement sessions.
• Validate requirements against data models, APIs, pipelines, and cloud infrastructure patterns.

Hands-on technical contribution

• Contribute to data analysis, SQL queries, schema definitions, metadata documentation, and pipeline validation.
• Support cloud modernization, cost optimization, and AI enablement initiatives.
• Create data contracts, business logic mappings, and quality rules for engineering implementation.
• Validate delivered solutions through hands-on testing, data reconciliation, and functional verification.

Data quality and delivery

• Define data quality checks, reconciliation logic, and reliability metrics in delivery workflows.
• Support automation of validation, monitoring, and reporting.
• Ensure observability, lineage, and governance considerations are addressed early.
• Reduce ambiguity and rework through technical documentation and support backlog prioritization.

Required technical experience

• Strong hands-on experience with SQL and data analysis across large datasets.
• Solid understanding of cloud data platforms such as AWS, Azure, or GCP.
• Familiarity with data lakes, lakehouses, ELT or ETL pipelines, and streaming or batch processing.
• Working knowledge of APIs, data integration patterns, and conceptual, logical, and physical data modeling.
• Working knowledge of data quality and reconciliation frameworks such as SODA.
• Comfort working in Agile and DevOps delivery models.

Product and collaboration skills

• Ability to connect business objectives to technical implementation details and reason through complex data and system interactions.
• Experience with product backlogs, user stories, and acceptance criteria.
• Ability to collaborate with engineering-heavy teams and document complex technical concepts clearly.
• Experience in data engineering, analytics engineering, or platform engineering teams is preferred.
• Exposure to automation, orchestration, or CI/CD pipelines is preferred.

Work arrangement

• Employees work in the office at least three days per week, with flexibility to work from home two days per week.
• Some roles may require additional in-office time or different expectations, which are discussed during hiring.

Schedule and employment

• The position is full time.
• The listed working hours are 2:00 p.m. to 10:30 p.m.