Senior Data Engineer - Cloud Analytics & ML Pipelines

CVS Health; Hartford (CT); On-site; USD 83,000 - 222,000; Full time

Job summary

CVS Health is seeking a Senior Data Engineer in Hartford to design and implement data pipelines powering analytics, reporting, and machine learning workloads. This hands-on role requires strong data engineering practices and the ability to translate business requirements into scalable technical solutions.

You will collaborate with data scientists and analysts to build robust data models, ETL/ELT processes, and optimized data infrastructure within a cloud environment (Azure, AWS, GCP).

Qualifications

• 5+ years of applicable data engineering work experience.
• Strong SQL skills and ability to write complex queries.
• Proficient in Python for ETL/ELT pipelines.
• Experience deploying pipelines in cloud environments (Azure/AWS/GCP).
• Knowledge of data governance best practices in the cloud.

Responsibilities

• Data Modeling & Architecture: develop data models and schemas for analytics and ML.
• Data Pipeline Development: design and build ETL/ELT pipelines from multiple sources.
• Performance Optimization: tune queries, partitioning, and clustering to reduce costs.
• Data Quality & Governance: enforce data quality, governance, and security policies.
• Data Integration & Transformation: collaborate with data scientists and analysts.
• Documentation & Knowledge Sharing: document pipelines and mentor juniors.
• Design and architect data infrastructure for analytical workloads with dimensional modeling.

Skills

5+ years experience

SQL

Python

Cloud (Azure/AWS/GCP)

Data governance

Education

Bachelor's degree

Job description

CVS Health is seeking a Senior Data Engineer in Hartford to design and implement data pipelines powering analytics, reporting, and machine learning workloads. This hands-on role requires strong data engineering practices and the ability to translate business requirements into scalable technical solutions.

You will collaborate with data scientists and analysts to build robust data models, ETL/ELT processes, and optimized data infrastructure within a cloud environment (Azure, AWS, GCP).