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Strong employer brand, generalist data engineering role, and metro hybrid location increase applicant competition.
Core data engineering skills (Python, SQL, ETL) are highly transferable across industries.
Explicit 7+ years, 2+ years leadership, and mandatory Airflow/Dataflow/Python/SQL requirements.
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Lead a squad of data engineers to build scalable ETL and Reverse ETL pipelines using Python, SQL, Airflow, and AI coding tools.
Standardize AI-driven development processes, including complex SQL transformations, Python scripts, query optimization, and unit testing for data quality.
Translate solution architect's data strategies and ERD designs into optimized physical tables and production-grade code with CI/CD implementation.
7+ years experience in Data Engineering, including 2+ years in a leadership role.
Expert proficiency in Python 3.x, advanced SQL (window functions, recursive CTEs), and AI tooling like GitHub Copilot or Claude Code.
3+ years experience with Apache Airflow and experience with Google Cloud Dataflow (Apache Beam) or similar managed cloud data processing services.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Experienced technical leader comfortable balancing code quality with business delivery velocity using AI tools.
Proven expertise in designing and optimizing large-scale data pipelines with emphasis on Data Lakehouse architecture and Reverse ETL.
Strong collaborator capable of translating architectural blueprints into highly performant, maintainable data systems and enforcing SQL governance.