Staff Systems Engineer – Digital

Job not on LinkedIn

🕒 July 20

⚓ Rhode Island – Remote

⚓ Rhode Island – Remote

💵 $130.3k - $260.6k / year

⏰ Full Time

🔴 Lead

⚙️ Systems Engineer

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CVS Health

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1963

🏥 Healthcare

⚕️ Healthcare Insurance

🛒 Retail

Healthcare • Healthcare Insurance • Retail

CVS Health is a leading American healthcare company dedicated to improving health access and affordability. The company focuses on a comprehensive approach that includes health services, health insurance, and pharmacy benefits management. Through its subsidiaries, such as Aetna and CVS Caremark, CVS Health offers a range of services that facilitate wellness, condition management, and affordable prescription drug coverage. CVS Health operates neighborhood pharmacies, provides mail-order pharmacy services, and manages specialty medication programs, aiming to make healthcare convenient and accessible for everyone. Driven by a mission to connect people with essential care services, CVS Health is committed to fostering healthier communities and supporting the wellbeing of all individuals.

📋 Description

• Define and own the enterprise data architecture strategy across operational, analytical, and AI/ML workloads • Design and govern data models, data contracts, and canonical schemas used across product and platform teams • Evaluate and standardize data platform tooling — data lakes, warehouses, streaming, and serving layers (GCP BigQuery, Pub/Sub, Dataflow, or equivalent) • Serve as the primary point of contact and SME for shared data platform concerns across teams • Own data governance frameworks including data classification, lineage, ownership, and quality standards • Partner with legal, security, and compliance teams to ensure data handling meets HIPAA, CCPA, and applicable healthcare regulatory requirements • Define and enforce data access control patterns, masking strategies, and PHI handling across the platform • Drive data catalog adoption and metadata management practices across engineering and analytics teams • Establish data retention, archival, and deletion standards aligned to regulatory and business requirements • Design data architectures that support AI/ML model training, feature engineering, and inference pipelines • Define feature store patterns and real-time data serving strategies for AI agent and recommendation systems • Partner with AI engineering teams to ensure data contracts and schemas are fit for LLM and generative AI use cases • Establish MLOps-adjacent data patterns — dataset versioning, training/serving skew detection, and model input monitoring • Partner closely with product engineering, platform, and analytics teams to understand data needs and deliver architectural solutions • Act as a technical advisor and escalation point for complex data architecture decisions across teams • Create and maintain clear documentation, data architecture decision records (ADRs), and onboarding guides for platform tools • Drive alignment on data standards, naming conventions, and shared data product strategies across teams • Establish data quality frameworks — schema validation, freshness SLAs, completeness checks, and anomaly detection • Define observability standards for data pipelines including alerting, lineage tracking, and incident response • Drive data reliability engineering practices that minimize data incidents and reduce mean time to resolution • Champion testing practices for data pipelines — unit, integration, and contract testing

🎯 Requirements

• 7+ years of experience in data engineering, data architecture, or related roles • 5+ years of hands-on experience with cloud-native data platforms - GCP (BigQuery, Dataflow, Pub/Sub), Azure Synapse • 5+ years of experience with data governance, compliance, and regulatory requirements • Proven track record of building and governing enterprise-scale data platforms across multiple product teams • Strong communication skills — able to translate complex data architecture decisions for technical and non-technical stakeholders • Deep expertise in relational and non-relational data modeling — dimensional modeling, Data Vault, or event-sourced patterns • Strong command of SQL and at least one data pipeline language (Python, Scala, or Spark) • Experience with streaming data architectures — Kafka, Pub/Sub, Kinesis, or equivalent • Experience with data governance tooling — Dataplex, Collibra, Alation, or similar • Familiarity with data mesh principles and federated data ownership models • Knowledge of feature store platforms (Feast, Tecton, Vertex AI Feature Store) for ML use cases • Experience with dbt, Great Expectations, or similar data transformation and quality frameworks • Exposure to LLM data pipelines — RAG architectures, embedding generation, or vector database design (Pinecone, Weaviate) • Experience supporting or leading data platform or data foundation teams in a multi-team organization • Bachelor's degree or equivalent experience (HS diploma + 4 years relevant experience)

🏖️ Benefits

• medical, dental, and vision coverage • paid time off • retirement savings options • wellness programs • comprehensive benefits package based on eligibility