Engineering Manager (Data Team)

5+ years of experience in a leadership role on a data team. Degree in Computer Science, Data Science, or related field. Extensive experience with DBT projects. Strong experience designing, scheduling, and monitoring Airflow data pipelines. Expert-level SQL skills and PostgreSQL performance tuning. Experience with Superset, Power BI, Looker, or Tableau. Strong Python proficiency for data pipelines and infrastructure. Basic working knowledge of Ruby. Demonstrated experience owning data accuracy and validation. Comfortable running agile sprints and managing a Kanban board. Excellent communication skills. Proactive and high-ownership mindset.

Manage and mentor the data engineering team. Organize and lead two-week sprints. Promote transparency and shared ownership through peer reviews. Communicate team progress to leadership. Define and execute the long-term vision for data engineering infrastructure. Establish and document workflows and development lifecycle. Take full ownership of the data stack (DBT, Airflow, Superset, PostgreSQL). Review and ensure quality of DBT PRs. Build, manage, and troubleshoot Airflow DAGs. Validate data accuracy and performance in Superset. Maintain, optimize, and scale PostgreSQL data warehouse. Write and review Python code for data pipelines. Design and guide scalable data models. Understand Ruby/Rails code for debugging. Ensure data accuracy before handoff to analytics. Keep DBT, Airflow, and Superset updated and manage issues.