Senior Engineering Manager, People Analytics

What you'll do

• Manage, coach, and grow a team of data engineers while setting expectations for quality and technical ownership.
• Write and review production code and lead technical design reviews for critical pipelines and AI workflows.
• Design and maintain sustainable data models, pipelines, semantic layers, and testing frameworks.
• Establish engineering standards for SQL, Python, dbt, Airflow, Snowflake, and CI/CD processes.
• Own the technical delivery for AI-assisted workforce analytics and internal tools.
• Enforce data governance policies to ensure integrity, security, and compliance for sensitive People data.
• Translate business requirements into scalable technical designs, delivery plans, and engineering milestones.

What we're looking for

• A bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
• 7+ years of experience in data engineering, analytics engineering, or data platform engineering.
• 5+ years of experience managing or formally leading engineers.
• Proficiency in Python, SQL, dbt, Airflow, and Gitlab.
• Proficiency in relational and cloud database platforms such as Snowflake, Redshift, or GCP.
• Experience designing dimensional models, semantic layers, data marts, or analytical data products.
• Experience with data quality, testing, lineage, observability, and production support.
• Experience with sensitive or regulated data and access controls.
• Experience in People analytics, HR data, compensation, talent, workforce planning, or Workday (preferred).
• Experience building AI, LLM, RAG, or natural language analytics products (preferred).
• Experience with Snowflake Cortex AI, Streamlit, semantic models, or evaluation frameworks (preferred).
• Experience in fintech, banking, or regulated environments (preferred).