#133206 - Senior Data Engineer

About this role

We are seeking a Senior 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 securely handling sensitive data at large scale. - Experience with real-time or near-real-time data processing from APIs, Google Sheets, or comparable sources. - Strong SQL skills, including highly optimized queries. - Comprehensive technical documentation skills. - Advanced English communication skills. Nice-to-Have Skills - Experience designing semantic layers or semantic models that provide business-object abstraction over dbt and warehouse models.