Lead Data Quality Engineer @ Pleasanton, CA (Onsite)

Technical Skills and Qualifications:

Google Cloud Platform Expertise: Proficient in Google Cloud Platform, Dataflow, Big Query, Cloud Composer, and Google Storage services.

Databricks: Experience with Spark-based data engineering workflows, including Delta Lake.

Testing Tools & Frameworks: Strong experience with tools like PyTest, dbt (data build tool), or similar testing frameworks for data pipelines.

SQL and Scripting: Advanced SQL skills for data validation with Python proficiency for automation.

Big Data Knowledge: Knowledge of Big Data processing and distributed computing. Understand the importance of data modelling concepts.

CI/CD: Knowledge of CI/CD pipelines on or GitHub Actions, focusing on data engineering workflows.

Data Governance: Familiarity with data governance tools and concepts such as metadata management, lineage, and data cataloging.

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