Description
This role will lead the data engineering function supporting People Analytics, including AI-assisted workforce analytics on Snowflake.
Responsibilities:
- Manage and develop data engineers
- Stay hands on
- Build scalable People data foundations
- Own engineering standards
- Support AI enabled analytics
- Balance speed and rigor
Requirements:
- A bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
- 7+ years in data engineering, analytics engineering, or data platform engineering.
- 5+ years managing or formally leading engineers.
- Proficiency in data engineering tech stack: 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, with the capability to simplify complex issues into actionable plans.
Preferred Experience:
- 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, semantic models, or evaluation frameworks
- Experience in fintech, banking, or regulated environments
Compensation and Benefits: The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location.