Senior Data Engineer

CVS Health•New York, NY

1d•Onsite

About The Position

The Senior Data Engineer within the AI Platform team is responsible for designing, building, and scaling enterprise-grade data pipelines and data services that power AI/ML applications, analytics, and operational intelligence use cases. The team focuses on enabling secure, high-quality, and real-time data access across enterprise platforms, including data ingestion, transformation, API integration, and feature engineering to support machine learning workflows. This role partners closely with AI/ML engineers, platform engineering (CAP/EDP), and product teams to develop scalable and compliant data solutions that support healthcare use cases, including handling PHI/PII data under strict governance and security standards. The position plays a key role in modernizing data platforms, enabling reusable data services, and improving performance, reliability, and observability of enterprise data systems.

Requirements

5+ years of experience in Data Engineering, Software Engineering, or related field
3+ years of hands-on experience developing ETL/ELT pipelines using tools/frameworks such as Spark, Databricks, or similar distributed processing systems
Strong proficiency in SQL and at least one programming language such as Python or Scala
Experience working with at least one cloud platform (AWS, Azure, or GCP)
Experience designing and implementing data pipelines for batch and/or streaming data processing
Experience with data modeling, data warehousing, or lakehouse architectures
Experience integrating systems using APIs, event-driven architectures (e.g., Kafka), or microservices
Experience implementing data quality, validation, and monitoring frameworks
Experience working with large-scale structured and unstructured datasets
Experience handling sensitive data (PHI/PII) or working in regulated environments
Experience using version control (e.g., Git) and CI/CD pipelines
Bachelor’s degree or equivalent work experience in Mathematics, Statistics, Computer Science, Engineering, or related discipline required

Nice To Haves

Strong problem-solving and analytical thinking skills
Ability to design scalable, reusable, and resilient data solutions aligned with enterprise platforms
Experience collaborating with cross-functional teams including AI/ML, product, and platform engineering
Familiarity with AI/ML workflows, feature engineering, and model data pipelines
Understanding of healthcare data domains such as claims, customer care, or clinical data
Knowledge of data observability, lineage, and monitoring best practices
Experience contributing to platform modernization initiatives (e.g., API gateway migration, data platform consolidation)
Ability to mentor junior engineers and contribute to technical design reviews
Strong communication skills with ability to translate business needs into technical solutions
Master’s degree preferred

Responsibilities

Designing, building, and scaling enterprise-grade data pipelines and data services.
Enabling secure, high-quality, and real-time data access across enterprise platforms.
Supporting machine learning workflows through data ingestion, transformation, API integration, and feature engineering.
Developing scalable and compliant data solutions that support healthcare use cases, including handling PHI/PII data under strict governance and security standards.
Modernizing data platforms.
Enabling reusable data services.
Improving performance, reliability, and observability of enterprise data systems.