Staff Data Engineer

CVS Health is dedicated to creating a more connected and compassionate health experience. They are seeking a Staff Data Engineer to communicate with business leaders, analyze data, and develop scalable systems to manage data effectively.

Responsibilities:

• Communicate with business leaders to help translate requirements into functional specification
• Develop broad understanding of business logic and functionality of current systems
• Analyze and manipulate data by writing and running SQL queries
• Analyze logs to identify and prevent potential issues from occurring
• Deliver clean and functional code in accordance with business requirements
• Consume data from any source, such a flat files, streaming systems, or RESTful APIs
• Engineer scalable, reliable, and performant systems to manage data
• Collaborate closely with other Engineers, QA, Scrum master, Product Manager in your team as well as across the organization
• Build quality systems while expanding offerings to dependent teams
• Comfortable in multiple roles, from Design and Development to Code Deployment to and monitoring and investigating in production systems

Requirements:

• 7+ years of relevant experience
• Proven ability to complete projects in a timely manner while clearly measuring progress
• Ability to use AI driven tooling
• Strong software engineering fundamentals (data structures, algorithms, async programming patterns, object-oriented design, parallel programming)
• Strong understanding and demonstrated experience with at least one popular programming language (.NET or Java) and SQL constructs
• Experience with cloud-based systems (Azure / AWS / GCP)
• High level understanding of big data design (data lake, data mesh, data warehouse) and data normalization patterns
• Strong communication skills
• Ability to collaborate closely with product, data analytics teams
• Proficiency in building scalable data pipelines on Big Data Platforms and ETL/ELT workflows
• 3+ years in senior or lead roles
• Expert-level skills in writing and optimizing complex queries (preferably across multiple databases – e.g., SQL Server, Snowflake, Postgres)
• Solid knowledge of Apache Kafka (Kafka Streams, Schema Registry, Avro/JSON serialization)
• Advanced experience building distributed data pipelines, ETL/ELT workflows, and real-time/streaming jobs (Spark SQL, PySpark, Spark Structured Streaming)
• Strong understanding of data modeling, data quality, and governance in regulated environments (HIPAA, HITRUST)
• Familiarity with Epic Interconnect APIs, Bridges, or other healthcare interoperability frameworks
• Experience with Azure (preferred), AWS, or GCP for data engineering workloads
• Experience working on Databricks platform
• Experience with DBT and Dagster
• Strong Python programming experience for data ingestion, transformation, and automation workflows
• Strong experience with revision control (Git)
• Demonstrated experience with Metrics, Logging, Monitoring and Alerting tools
• Strong experience with use of RESTful APIs
• High level understanding of system deployment tasks and technologies. (CI/CD Pipeline, K8s, Terraform)
• Experience designing real-time streaming pipelines and batch workflows