Staff Systems Engineer - Digital

Job Title: Staff Systems Engineer - Digital Job Location: Work at Home, Rhode Island, United States Job Location Type: Remote Job Contract Type: Full time Job Seniority Level: 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 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.

You will be the primary authority on how information is modeled, governed, and served across operational, analytical, and AI workloads - driving quality, compliance, and reliability at scale. If you thrive in a role where your architecture decisions multiply the productivity and capability of entire teams, this is the opportunity for you.

Key Responsibilities: 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

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

Required Qualifications

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

Preferred Qualifications

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) Pay Range The typical pay range for this role is: $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. 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: 07/31/2026 Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws. This job is curated by Lifelancer . Lifelancer is a talent-hiring platform in Life Sciences, Pharma and IT.

The platform connects talent with opportunities in pharma, biotech, health sciences, healthtech and IT domains. Please apply via Lifelancer platform to get connected to the application page and to find similar roles. Originally posted on Himalayas