Senior Data Engineer, People Analytics

Responsibilities

• Collaborate with stakeholders to translate data- and people-related business problems into scalable data solutions
• Build data pipelines and tables from HR systems such as Workday, Greenhouse, and other data sources
• Support Data Science team members in leveraging data for reporting, dashboard development, and client-facing use-cases
• Build, update, and maintain a production-grade data foundation that supports AI initiatives — including pipelines that feed LLM-powered tools, evaluation and feedback datasets, and access controls and data models
• Design and deliver data products, including dashboards and reporting tools (e.g., Streamlit visualization apps)
• Write and optimize queries across Trino/Presto and Postgres
• Align on priorities and work from a roadmap
• Assess data readiness for AI use cases, working with EX teams, Legal, and BizTech to ensure sensitive employee data is handled with appropriate governance, permissioning, and access controls
• Support the transition of AI prototypes to production by building underlying infrastructure

Requirements

• 5+ years of industry experience as a Data Engineer
• Highly proficient in SQL across OLAP and OLTP environments (Trino/Presto/Hive, Postgres)
• Strong command of Ubuntu environment and ability to manage files on AWS instances through SSH
• Experience working with relational databases and assuming an administrative role
• Fluent in Python with ability to interact with data sources (web APIs, SFTP, S3 buckets, Airtable)
• Experience with scalable data pipelines leveraging Airflow or similar orchestration frameworks
• Proficiency in database concepts: primary key, index, nullable fields, data types, partitioning; experience designing data models
• Prior work experience with sensitive data including sensitivity classification, access controls, and audit logging
• Experience building data products, dashboards or reporting tools using Streamlit
• Ability to analyze large data sets, identify gaps, interpret complex queries, and communicate findings to non-technical audiences
• Experience building data layers that support LLM-based tooling or agentic AI frameworks
• Strong cross-functional collaboration skills with technical and non-technical stakeholders
• Solid understanding of data structures & algorithms
• Proficiency with Git for code base management and version control
• Familiarity with system design principles for data platforms or AI-integrated systems

Nice-to-Haves

• Experience with data governance requirements for employee or sensitive data
• Experience mentoring and supporting peers