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SoFi is seeking a Senior Engineering Manager to lead the data engineering function supporting People Analytics. This is a player-coach role combining hands-on technical leadership with people management, requiring strong business partnership and the ability to balance speed, quality, governance, and innovation.
You will manage and develop a team of data engineers, setting expectations for quality, collaboration, delivery, and technical ownership. You'll create a strong engineering culture where the team solves hard problems, moves quickly, and enjoys the work. You'll collaborate with cross-functional teams including 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.
This role requires staying hands-on: writing and reviewing production code, leading design and code reviews, technical problem-solving, and stepping into critical pipelines, models, or AI workflows when needed.
Key responsibilities include designing and maintaining sustainable data models, pipelines, semantic layers, and testing frameworks; establishing team practices for documentation, lineage, data quality, and observability; setting standards for SQL, Python, dbt, Airflow, Snowflake, testing, documentation, CI/CD, and release management; and ensuring the team ships reliable, maintainable, secure, and understandable work.
You'll own technical delivery for AI-assisted workforce analytics and internal tools, translating business needs into scalable technical designs and delivery plans. You'll partner with People Analytics, People leaders, Legal, Compliance, and other stakeholders to deliver trusted workforce insights, including work on semantic models, evaluation datasets, testing, and quality controls for AI-assisted analytics.
Required: Bachelor's degree in Computer Science, Data Science, Engineering, or related field; 7+ years in data engineering, analytics engineering, or data platform engineering; 5+ years managing or formally leading engineers; proficiency in Python, SQL, dbt, Airflow, GitLab; experience designing dimensional models, semantic layers, data marts, or analytical data products; experience with data quality, testing, lineage, observability, and production support; strong ability to translate business needs into technical architecture; experience with sensitive or regulated data and access controls; proven ability to coach engineers and build healthy technical culture; strong communication with technical and non-technical stakeholders; proficiency in relational and cloud database platforms such as Snowflake, Redshift, or GCP; thorough knowledge of data modeling, database design, data architecture principles, data operations, and CI/CD; strong analytical and problem-solving abilities.
Preferred: People analytics, HR data, compensation, talent, workforce planning, or Workday experience; experience building AI, LLM, RAG, or natural language analytics products; experience with Snowflake Cortex AI, Streamlit.
