Google Cloud Platform Data Engineer

#W2 role

Role: Senior Google Cloud Platform Data Engineer
Location:Remote
Experience: 8 years

Our client is looking for an experienced Google Cloud Platform Data Engineer to build and support cloud-based data solutions for healthcare, pharmacy, claims, member, and operational data.

This is a hands-on development role. The engineer will work with architects, analysts, product owners, and other engineering teams to build reliable batch and real-time data pipelines on Google Cloud Platform.

• Design, develop, and maintain scalable data pipelines using Google Cloud Platform services.

• Build batch and streaming solutions using Dataflow, Pub/Sub, BigQuery, Cloud Storage, Dataproc, and Cloud Composer.

• Develop data-processing applications using Python, SQL, Spark, and Apache Beam.

• Create BigQuery tables, views, stored procedures, and data models.

• Apply partitioning and clustering strategies to improve BigQuery performance and cost.

• Ingest and transform healthcare, pharmacy, claims, member, provider, and operational data.

• Build data validation, reconciliation, error-handling, and monitoring processes.

• Troubleshoot pipeline failures, data-quality issues, and performance problems.

• Support data migration from legacy and on-premises platforms to Google Cloud Platform.

• Protect PHI, PII, and other sensitive information using appropriate security and access controls.

• Develop automated build and deployment pipelines using Git, Jenkins or GitLab CI/CD, and Terraform.

• Participate in code reviews, production releases, and operational support.

• 8 years of data engineering or software development experience.

• 4 years of hands-on experience with Google Cloud Platform data services.

• Strong experience with BigQuery, Dataflow, Pub/Sub, Cloud Storage, Dataproc, and Cloud Composer.

• Advanced Python and SQL development skills.

• Experience with Spark, Apache Beam, and Airflow.

• Strong understanding of ETL/ELT, data warehousing, data lakes, and distributed data processing.

• Experience building both batch and streaming data pipelines.

• Experience with Docker, Kubernetes, Terraform, Git, and CI/CD.

• Strong troubleshooting and communication skills.

• Healthcare, pharmacy, PBM, claims, or health insurance experience.

• Understanding of HIPAA, PHI, and PII requirements.

• Experience with dbt, Dataplex, Data Catalog, Cloud Run, Cloud Functions, or Looker.

• Google Professional Data Engineer certification.