#136209 - Data Engineer - HR Analytics & AI-Ready Data

Summary We are seeking an experienced Data Engineer to build and maintain secure, reliable, and scalable data pipelines, warehouse models, and analytical datasets supporting people insights.

This role combines hands-on data engineering with data modeling, platform reliability, semantic-layer design, and governed access for both business intelligence tools and AI-enabled interfaces. Enterprise experience strongly preferred.

Key Responsibilities

Develop and maintain secure, efficient data pipelines using dbt, PySpark, and Python applications. Build extraction, transformation, and loading infrastructure using Python, dbt, Terraform, AWS Glue, Amazon EMR, and Amazon S3. Integrate data from APIs, cloud systems, Google Sheets, and other structured sources.

Create and maintain Snowflake warehouse models, datamarts, and analytics-ready datasets. Develop automated data-quality tests and improve internal data-engineering processes. Monitor production pipelines and help maintain a 99. 5% uptime objective.

Design semantic views, ontology layers, business-friendly entities, relationships, and certified metrics over warehouse models. Build governed natural-language data experiences using Snowflake Cortex Analyst, Cortex Search, or equivalent LLM-native query layers.

Configure secure Model Context Protocol connections or comparable interfaces between governed data sources and internal AI tooling. Document data models, pipelines, business logic, operational procedures, and technical decisions comprehensively. Must-Have Skills 5+ years of relevant experience.

Hands-on Snowflake experience, including data modeling, datamarts, and data warehouse design. Hands-on dbt experience for data transformations. Strong Python experience, including object-oriented programming and data scripting. Hands-on Airflow experience for pipeline orchestration.

Experience integrating REST APIs and ingesting data from external sources. Hands-on Google BigQuery querying and optimization experience. Experience