Data Engineer

Data Engineer

We're building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you'll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time.

We are seeking a highly skilled Data Engineer to support enterprise data platforms that enable analytics, AI-driven insights, member communications, and business intelligence capabilities. This role requires deep hands-on expertise in Google Cloud Platform (GCP), modern data engineering frameworks, cloud-native architectures, and enterprise data governance.

The ideal candidate will have experience delivering scalable data solutions in GCP, building large-scale batch and streaming pipelines, and supporting healthcare or financial services organizations. As a Data Engineer, you will collaborate with architects, product owners, data scientists, and business stakeholders to design, develop, and optimize secure, reliable, and high-performing data platforms in a regulated environment.

Key Responsibilities

Data Engineering & Pipeline Development

• Design, develop, and maintain scalable batch and real-time data pipelines using GCP services including BigQuery, Dataflow, Pub/Sub, Cloud Composer, Cloud Functions, and Cloud Run.
• Build reusable and maintainable ingestion, transformation, and orchestration frameworks using Python, SQL, Spark/PySpark, Apache Beam.
• Develop data integration solutions leveraging APIs, event-driven architectures, and cloud-native services.

Cloud Data Platform Development

• Build and support enterprise-grade data lake, data warehouse, and streaming solutions across GCP and AWS cloud platforms.
• Independently design, develop, and deploy cloud-native data products supporting analytics, reporting, AI/ML, and operational workloads.
• Participate in enterprise cloud migration initiatives and modernization efforts, helping define migration strategies and implementation roadmaps.

Data Architecture & Modeling

• Design and implement logical and physical data models using Star Schema and Snowflake Schema methodologies.
• Develop scalable solutions supporting BigQuery, Snowflake, Redshift, Teradata, and other enterprise analytical platforms.
• Optimize partitioning, clustering, indexing, and storage strategies to improve performance and cost efficiency.

Streaming & Real-Time Processing

• Build and maintain high-throughput streaming data solutions using Pub/Sub, Kafka, Dataflow, Spark Structured Streaming, Apache Beam, and Apache NiFi.
• Support near real-time data processing requirements across business and operational domains.

Data Governance & Compliance

• Implement enterprise-grade governance solutions using tools such as Collibra, Privacera, Unity Catalog, and related governance frameworks.
• Ensure compliance with HIPAA, GDPR, PCI-DSS, and corporate security standards through robust access controls, lineage tracking, auditing, encryption, and data protection practices.
• Support metadata management, data quality monitoring, and data lineage initiatives across the enterprise.

Performance, Reliability & Operations

• Monitor, troubleshoot, and optimize enterprise data pipelines and cloud infrastructure.
• Implement observability using Cloud Monitoring, logging, alerting, and automated recovery solutions.
• Create data flow documentation, technical design artifacts, production support procedures, and root cause analyses (RCA).

Collaboration & Delivery

• Collaborate with business stakeholders, architects, product managers, and engineering teams to deliver scalable data solutions.
• Participate in Agile and SAFe delivery frameworks across onshore and offshore teams.
• Communicate complex technical concepts effectively to both technical and non-technical stakeholders.

Core Technical Skills

Cloud Platforms

• Google Cloud Platform (GCP)
• BigQuery
• Dataflow
• Pub/Sub
• Cloud Composer
• Cloud Functions
• Cloud Run
• Cloud Storage
• Cloud Monitoring

Data Engineering & Processing

• Python
• SQL
• PySpark
• Apache Spark
• Apache Beam
• Apache Kafka
• Apache NiFi
• StreamSets
• Hadoop Ecosystem

Data Warehousing & Analytics

• BigQuery
• Snowflake
• Teradata
• Star Schema Design
• Snowflake Schema Design

Databases

• PostgreSQL
• SQL Server
• Oracle (PL/SQL)
• Hive
• MongoDB Atlas

Workflow Orchestration

• Apache Airflow
• Cloud Composer

DevOps & CI/CD

• Git
• GitHub Actions
• GitLab CI/CD
• Terraform

Required Qualifications

• 5+ years of professional experience in Data Engineering, Data Platforms, or Data Integration.
• 3+ years of hands-on experience with Google Cloud Platform data services.
• 3+ years designing, developing, and supporting large-scale batch and streaming data pipelines.
• Strong expertise in Python, SQL, Spark/PySpark, Apache Beam, BigQuery, Dataflow, Pub/Sub, and Cloud Composer.
• Experience with enterprise data warehouse platforms including BigQuery, Snowflake, Redshift, or Teradata.
• Experience with data modeling, data architecture, and distributed systems.
• Experience implementing CI/CD pipelines and Infrastructure as Code using Terraform, Git, and cloud-native deployment tools.
• Experience working in Agile and SAFe delivery environments.
• Strong analytical, troubleshooting, documentation, and problem-solving skills.

Preferred Qualifications

• Healthcare or Insurance industry experience.
• Experience with data governance platforms including Collibra, Privacera, or Unity Catalog.
• Experience supporting AI/ML, analytics, and data science workloads.
• Experience with MongoDB Atlas and NoSQL data platforms.
• Experience building real-time streaming architectures using Kafka and Pub/Sub.
• Experience creating Data Flow Diagrams, operational runbooks, and RCA documentation.
• Experience with reporting and visualization tools including Power BI, Tableau, QlikView, or Looker.
• Experience collaborating across global onshore/offshore engineering teams.

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or a related field, or equivalent combination of education and relevant professional experience.

Anticipated Weekly Hours

40

Time Type

Full time

Pay Range

The typical pay range for this role is:

$79,310.00 - $158,620.00

This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above.

Additional details about available benefits are provided during the application process and on Benefits Moments.

We anticipate the application window for this opening will close on: