Description

Responsibilities

Design, develop, and maintain scalable data pipelines using GCP 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 GCP.

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.

Required Qualifications

8+ years of data engineering or software development experience.

4+ years of hands-on experience with GCP 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.

Preferred Qualifications

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

Key Skills

Education

Bachelor’s degree