Staff Systems Engineer - Digital

CVS Health
United States
26 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
4 years minimum
Compensation
$130,295.0 - $260,590.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Systems Engineering BigQuery Data Architecture Information Engineering Data Governance Data Infrastructure Data Transformation Data Retention Data Security Data Sharing Data Vault Modeling
+28 more
Relational Databases Database Design Dimensional Modeling Data Flow Control Python (Programming Language) Machine Learning Meta-Data Management Recommender Systems Cloud Services SQL Databases Data Streaming Management of Software Versions Data Processing Data Classification Feature Engineering Delivery Pipeline Large Language Models Apache Spark Data Lakes Collibra Ripple (payment Protocol) Real Time Data Apache Kafka Data Management Machine Learning Operations Virtual Agents Azure Synapse Analytics Data Pipelines

Job description

We are looking for a Staff Systems Engineer - Digital to join our team, the foundational layer that powers access, governance, and intelligence across our digital products. You will work horizontally across engineering, product, and AI teams, leading, owning, and evolving the shared infrastructure that every team at the company depends on., Data Architecture & Platform Ownership:

  • 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
  • Lead technical design and solutioning for foundational data components and cross-cutting data concerns

Data Governance & Compliance:

  • 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

AI & Advanced Analytics Enablement:

  • 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

Cross-Team Collaboration & Enablement:

  • 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

Quality, Observability & Reliability:

  • 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

What We’re Looking For:

  • Beyond technical skills, we are looking for someone who:
  • Thinks in systems - you see how data decisions ripple across platforms, teams, and downstream consumers
  • Communicates with clarity - written and verbal, across engineering, product, and executive audiences
  • Is proactive - you identify data quality and architecture risks before they become production incidents
  • Takes ownership - you see architecture decisions through from design to documentation to adoption
  • Is collaborative by nature - you raise the data maturity of teams around you, not just your own

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

Education:

  • Bachelor’s degree or equivalent experience (HS diploma + 4 years relevant experience)

Benefits & conditions

$130,295.00 - $260,590.00

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. This position also includes an award target in the company’s equity award program.

Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.

Great benefits for great people

We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families.

This full-time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well-being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.

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