Senior Software Development Engineer

CVS Health•Irving, TX

3d•$92,700 - $185,400

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. Position Summary We are seeking a highly skilled Senior Software Development Engineer/GCP Data Engineering resource to serve as the senior engineer for enterprise data platforms supporting AI-driven insights, member communications. This role requires deep hands-on expertise in Google Cloud Platform, combined with strong technical leadership, data architecture ownership, and cross-team collaboration. As a Data Engineering Lead , you will lead complex data engineering initiatives across GCP, set engineering standards, and partner closely with architects, product owners, and business stakeholders to deliver scalable, secure, and high-performance data solutions in a regulated healthcare environment.

Requirements

GCP Data Platform Development: Hands-on development using BigQuery, Cloud Dataflow, Pub/Sub, Cloud Composer (Airflow), and Cloud Functions to build scalable data pipelines.
Data Engineering & Pipelines: Build and manage batch and streaming pipelines using Python, PySpark, SQL, and Apache Beam for high-volume data processing.
Integrations & APIs: Implement event-driven architectures using Pub/Sub/Kafka and integrate with multiple systems (Cloud SQL, Firestore, MongoDB, external APIs).
CI/CD & DevOps: Able to use enterprise configured CI/CD pipelines using GitHub Actions, Jenkins, and Cloud Build; implement infrastructure as code using Terraform.
Performance Optimization: Optimize SQL queries, partitioning strategies, and pipeline performance for large-scale datasets and real-time processing.
AI & Advanced Analytics Enablement: Support AI/ML pipelines using Vertex AI, BigQuery ML, and advanced data orchestration tools for analytics use cases.
5+ years of professional software/data engineering experience with strong hands-on experience in GCP
3+ years building and managing large-scale data pipelines (batch + streaming)
3+ years strong expertise in: Python, SQL, Spark/PySpark, BigQuery, Dataflow, Pub/Sub, Cloud Composer
3+ years experience with CI/CD, DevOps, and infrastructure as code (Terraform)
3+ years experience working in Agile/Scrum environments
3+ years of data architecture, data modeling, and distributed systems

Nice To Haves

Experience in Healthcare, Insurance
Experience with MongoDB atlas
Experience working on large-scale analytics or AI-driven platforms
Familiarity with data governance tools and frameworks (Data Catalog, lineage, quality frameworks)
Exposure to streaming technologies (Kafka, Pub/Sub)
Experience with visualization tools such as Looker, Tableau, or Power BI

Responsibilities

Technical Leadership: Act as the senior technical lead for Project Data Assets in GCP data platform , owning data engineering standards, and complex implementation decisions across batch and streaming pipelines.
Healthcare & Compliance: Ensure data solutions comply with healthcare and regulatory standards (e.g., HIPAA, PCI-DSS, GDPR), implementing secure access, encryption, and governance controls.
Architecture & Design: Design scalable data pipelines using GCP services (BigQuery, Dataflow, Pub/Sub, Composer), supporting analytics, reporting, and AI/ML workloads.
Data Engineering & Pipelines: Develop and maintain data pipelines for batch and real-time data ingestion, transformation, and delivery using Python, Spark, and GCP-native technologies.
Performance & Reliability: Optimize performance, scalability, and reliability of large-scale data pipelines, implementing monitoring, logging, and failure recovery mechanisms.
Mentorship & Governance: Mentor onshore and offshore engineers, conduct design/code reviews, and enforce best practices in data engineering, DevOps, Production Support team onshore and offshore.