About the role
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Who we are
Shape a brighter financial future with us.
Together with our members, we’re changing the way people think about and interact with personal finance.
We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
Role Summary
We are looking for a talented and detail-oriented Sr Data Engineer to tackle data challenges. You will design, build, and maintain critical data pipelines and datasets, supporting areas like recruiting, compensation, talent management, and learning and development. Your work will enhance data accessibility and empower the People Team and business leaders to make informed decisions with high-quality, reliable data.
Key Responsibilities
- Develop and maintain robust data pipelines and datasets.
- Build foundational data products for key business areas.
- Enhance self-service data capabilities for the People Team.
- Ensure high standards in ETL/ELT operations, data quality, and pipeline reliability.
Join us to drive impactful change and support SoFi's mission of fostering a thriving workplace through data excellence.
What you’ll do
- Design and build production dbt models in Snowflake that integrate Workday and other People systems into well-modeled, documented datasets, including slowly changing dimensions for People history.
- Build and operate Airflow DAGs that ingest People systems data and orchestrate dbt runs, keeping loads reliable and re-runnable.
- Own data quality and observability: dbt tests, freshness checks, row-count validation, and monitoring so issues are caught before stakeholders see them.
- Implement and maintain row-level security and access controls for People data, partnering with governance and security teams.
- Build and maintain semantic models and AI agents, held to the same modeling, access, and quality standards as our pipelines.
- Collaborate with cross-functional teams, such as other data engineers, people analysts, data scientists, and business stakeholders, to translate requirements into production-ready deliverables, and communicate technical trade-offs to non-technical partners.