Data Engineer with GCP experience

CVS Health•Work At Home-Florida, FL

1d•$72,100 - $144,200

About The Position

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. The Data Engineer is responsible for designing, building, and supporting scalable data pipelines, data models, and analytical data assets that enable clinical, operational, financial, and strategic decision-making across CVS Health's healthcare delivery organizations. This role supports enterprise analytics initiatives spanning MinuteClinic, Virtual Care, Behavioral Health, Oak Street Health, and additional healthcare business domains. The position partners closely with data engineers, analytics teams, business stakeholders, clinicians, and product owners to deliver trusted, high-quality data solutions. The team manages the ingestion, transformation, and delivery of data from Epic Clarity, Epic Caboodle, Workday, retail healthcare platforms, vendor systems, and other enterprise data sources into Google Cloud Platform (GCP) and BigQuery-based analytics environments. This includes developing automated ETL/ELT pipelines, supporting cloud modernization initiatives, maintaining production data operations, ensuring data quality and governance standards, and enabling advanced analytics, AI, and reporting solutions. This role will help solve complex healthcare data challenges including large-scale data migration, integration of clinical and operational datasets, pipeline automation, reporting modernization, production support, and the delivery of reliable data products that support patient care, operational excellence, regulatory reporting, and business growth.

Requirements

Bachelor's degree or equivalent work experience in Computer Science, Information Systems, Engineering, Mathematics, Statistics, Data Science, Analytics, or related field.
4+ years of experience in Data Engineering, ETL Development, Analytics Engineering, Business Intelligence, or related technical roles.
3+ years of hands-on SQL development experience.
2+ years of experience building and supporting ETL/ELT pipelines.
Experience working with cloud platforms such as Google Cloud Platform (GCP)
Experience developing solutions using Python, PySpark, Spark, or similar data engineering technologies.
Experience with orchestration and scheduling tools such as Airflow, Control-M, Tidal, or equivalent.
Experience with relational database platforms such as SQL Server, PostgreSQL, BigQuery, Snowflake, or similar technologies.
Experience designing, developing, and supporting large-scale data integration solutions.
Experience working with source control and CI/CD practices.
Experience troubleshooting and supporting production data pipelines.
Experience implementing data quality validation, reconciliation, and monitoring processes.
Experience supporting healthcare, clinical, financial, or operational reporting environments.

Nice To Haves

Experience working with Epic Clarity, Epic Caboodle, Cogito Data Model, or healthcare EHR data platforms.
Experience supporting healthcare analytics, population health, quality reporting, revenue cycle, provider operations, or clinical reporting environments.
Understanding of Epic healthcare data structures, healthcare data workflows, and healthcare business processes.
Experience supporting Google Cloud Platform data services including BigQuery, Composer (Airflow), Dataflow, Dataproc, Cloud Storage, and related technologies.
Experience with AI-enabled software development, automation, or data engineering solutions.
Strong analytical and problem-solving skills.
Ability to communicate effectively with both technical and non-technical stakeholders.
Experience working in Agile and product-based delivery models.
Demonstrated ability to balance multiple priorities while maintaining high-quality deliverables.
Strong documentation, knowledge-sharing, and collaboration skills.
Experience mentoring junior engineers and contributing to engineering best practices
Experience with data governance, metadata management, and data lineage concepts.
Experience supporting large-scale data migration, cloud modernization, or reporting modernization initiatives.
Master's degree preferred.

Responsibilities

Designing, building, and supporting scalable data pipelines, data models, and analytical data assets.
Enabling clinical, operational, financial, and strategic decision-making across CVS Health's healthcare delivery organizations.
Supporting enterprise analytics initiatives spanning MinuteClinic, Virtual Care, Behavioral Health, Oak Street Health, and additional healthcare business domains.
Partnering closely with data engineers, analytics teams, business stakeholders, clinicians, and product owners to deliver trusted, high-quality data solutions.
Managing the ingestion, transformation, and delivery of data from various enterprise data sources into Google Cloud Platform (GCP) and BigQuery-based analytics environments.
Developing automated ETL/ELT pipelines.
Supporting cloud modernization initiatives.
Maintaining production data operations.
Ensuring data quality and governance standards.
Enabling advanced analytics, AI, and reporting solutions.
Solving complex healthcare data challenges including large-scale data migration, integration of clinical and operational datasets, pipeline automation, reporting modernization, and production support.
Delivering reliable data products that support patient care, operational excellence, regulatory reporting, and business growth.