Staff Data Infrastructure Engineer Hybrid Role
Posted
Summary
Staff-level data infrastructure engineer at a wholesale marketplace platform, steering data movement from production databases (CockroachDB, MySQL) into analytics (Snowflake, Databricks). Day to day: building Kafka/CDC ingestion layers, data quality checks and contracts, managing Airflow/Fivetran, and mentoring engineers. Hybrid role based in Kitchener, Canada.
Drive innovation in data at a tech wholesale platform as a Staff Data Infrastructure Engineer. This hybrid position focuses on streamlining data flow and enhancing quality controls for data systems.
Join a dedicated engineering team that powers the company's thriving marketplace. You'll steer the technical direction of data movement from production databases like CockroachDB and MySQL to analytic environments like Snowflake and Databricks. Key responsibilities include building ingestion layers, setting SLAs, and mentoring fellow engineers for effective data management.
Key Responsibilities: • Set technical direction for data movement into analytics • Build CDC and streaming ingestion layers using Kafka • Implement data quality checks and data contracts • Manage Airflow and Fivetran operations effectively • Ensure platform reliability through SLOs and incident reviews
Requirements: • Experience with change data capture and Apache Kafka • Strong knowledge of lakehouse architectures and Iceberg • Proficient in Spark, Databricks, and Snowflake • Solid Python skills plus experience with AWS tools • Understanding of data governance and cross-team leadership
Elevate your data engineering skills and make a significant impact at this innovative company.
Join a dedicated engineering team that powers the company's thriving marketplace. You'll steer the technical direction of data movement from production databases like CockroachDB and MySQL to analytic environments like Snowflake and Databricks. Key responsibilities include building ingestion layers, setting SLAs, and mentoring fellow engineers for effective data management.
Key Responsibilities: • Set technical direction for data movement into analytics • Build CDC and streaming ingestion layers using Kafka • Implement data quality checks and data contracts • Manage Airflow and Fivetran operations effectively • Ensure platform reliability through SLOs and incident reviews
Requirements: • Experience with change data capture and Apache Kafka • Strong knowledge of lakehouse architectures and Iceberg • Proficient in Spark, Databricks, and Snowflake • Solid Python skills plus experience with AWS tools • Understanding of data governance and cross-team leadership
Elevate your data engineering skills and make a significant impact at this innovative company.
