Data Engineer - GCP/AI/ML: CVS Health

As a Data Engineer at CVS Health, you will be part of the Data and Analytics organization, responsible for designing, building, and maintaining best-in-class data engineering pipelines on cloud platforms like GCP or Azure. Leveraging CVS Health's rich healthcare data for over 150 million individuals, you will collaborate with cross-functional teams, including data scientists and software engineers, to ensure the efficient and reliable processing, storage, and retrieval of data to drive best-in-class solutions.

Responsibilities
Manage and support the production platform to ensure the quality, performance, and availability of services.

Identify, design, and implement engineering process improvements by automating manual processes and optimizing data pipelines.

Provide 24/7 on-call support for the cloud production environment.

Work hands-on with customers to develop, migrate, and debug service issues.

Build data pipelines using the Azure/GCP platform.

Ensure server and process documentation is up-to-date.

Requirements
Required Qualifications:

1-2 years of related work experience.

Experience with cloud platforms: Azure and/or GCP (BigQuery, GCS, Pub/Sub, DataProc, Airflow/Composer, Snowflake).

Proficiency in Unix/Shell scripting.

Hands-on experience with Python and SQL.

Experience building robust data pipelines focused on data integration and quality.

Exposure to AI/ML workflows and the Gen AI Tech stack (OpenAI API).

Preferred Qualifications:

A cloud certification in data engineering (Azure or GCP preferred).

Strong programming skills in Python, PySpark, and SQL.

Deep understanding of query optimization, data structures, and workload orchestration.

Familiarity with CI/CD pipelines, DevOps best practices, Kubernetes, and containerized services.

Domain knowledge in Retail, Healthcare, or Insurance.

Experience supporting AI/ML initiatives (e.g., feature engineering, model deployment pipelines) and familiarity with AI frameworks (TensorFlow, PyTorch) and libraries (scikit-learn, MLflow).

Education:

A bachelor's degree or equivalent work experience in a STEM field (Computer Science, Engineering, etc.) is required. A Master's degree or PhD is preferred.