Senior Data Engineer - IGEN

Position Summary

The Senior Data Engineer is the technical leader for IGEN's Data Foundation, architecting, building, and operating the Snowflake data platform, Azure-native ingestion infrastructure, and governed data products that the broader organization depends on for trusted decision‑making and AI‑powered capability. The role owns the architectural integrity of the platform—ingestion patterns, transformation frameworks, schema governance, lineage, and pipeline SLAs—and partners directly with the Director, Data & Analytics on platform strategy.

It operates with AI‑assisted development, builds within the broader Microsoft and Azure ecosystem, and mentors Data Engineers as the function scales. The position works inside the AI governance framework developed in partnership with U.S. Venture Legal, Info Sec, Privacy, and Compliance, ensuring the data foundation supports IGEN's SOC 2 Type 2 obligations and the responsible deployment of AI capabilities across the platform.

IGEN is a division of U.S. Venture, a leading tax compliance software company trusted by industry leaders. The tax compliance platform, powered by a data engine, provides tools for reducing redundancy, managing risk, and handling tax compliance across the organization.

• Lead the design and implementation of enterprise‑grade data pipelines on Snowflake and Azure, owning ingestion, transformation, and serving layers for governed data products that support leadership reporting, client experience analytics, product usage analytics, and the regulatory intelligence pipeline.
• Architect ingestion and integration patterns across IGEN's source systems—including operational databases, SaaS platforms, regulatory data sources, and product telemetry—applying CDC, batch, and streaming patterns where appropriate.
• Establish and maintain transformation frameworks using dbt as the modeling standard, define layering and naming conventions, and ensure all pipelines are version‑controlled, tested, and observable.
• Own pipeline SLAs across the platform—defining and tracking freshness, completeness, and error‑rate targets for every data product, with documented runbooks and on‑call rotation for production‑critical pipelines.
• Drive schema governance and data modeling discipline—including conceptual, logical, and physical data models, naming conventions, and the management of breaking changes across consuming Power BI dashboards and downstream AI capabilities.
• Implement and maintain data lineage, catalog, and metadata management—ensuring every governed KPI has a traceable source, definition, owner, and certification status.
• Partner with the Director, Data & Analytics on the Center of Excellence operating model—intake processes, prioritization, stakeholder reviews, and the technical roadmap for the data platform.
• Use AI development assistants—Git Hub Copilot, Microsoft Copilot, Claude, and emerging agent‑based tooling—as a standard part of daily engineering practice, applying sound judgment in reviewing, validating, and securing AI‑generated transformation logic and pipeline code.
• Design and operate the regulatory intelligence pipeline—ingesting jurisdictional updates from federal, state, and local sources and structuring them for downstream AI‑assisted change‑impact analysis against Comply
  
  IQ, Tax Determination, and Reconciliation modules.
• Implement data security, privacy, and compliance controls aligned with SOC 2 Type 2 obligations and the AI governance framework—data classification, access controls, encryption at rest and in transit, PII handling, and audit trail requirements—partnering with U.S. Venture Info Sec, Privacy, and Compliance as required.
• Drive engineering best practices across the data function—CI/CD for data, version control, automated testing of transformation logic, observability, and incident response.
• Mentor Data Engineers—through code review, architectural pairing, and knowledge sharing—and contribute to the growth of the team's technical capability as IGEN scales the function.
• Optimize cost and performance across the Snowflake platform—warehouse sizing, query optimization, storage management, and chargeback visibility for…