Data Engineer (Data Quality and Data Governance)

Experience: 7+ years of hands-on data engineering experience, with a strong focus on data quality, data governance, and data pipeline reliability. Core Tech Stack: Expert-level proficiency in Python, SQL, and PySpark. Cloud Infrastructure: Extensive hands-on experience building production data architectures on AWS (e.g., S3, Glue, EMR, Redshift, Athena, Lambda). Data Quality Frameworks: Direct experience developing data checks and using data quality/contract tools like Soda, Gable, Great Expectations, or custom automated frameworks. Data Modeling & Architecture: Strong knowledge of data warehousing, lakehouse architectures, schema evolution, and data contract implementations. Engineering Standards: Experience with software engineering best practices, including Git, CI/CD pipelines, containerization (Docker), and orchestration tools (e.g., Apache Airflow, Prefect, or Dagster).