
Staff Systems Engineer - Digital
Immigration summary
Visa sponsorship
This employer has recently sponsored work like this.
1,385 recent H-1B filings
View visa evidenceGreen card sponsorship
This employer has recently sponsored green cards at scale.
133 recent certified PERM filings · 11 similar-role filings
View green card evidenceJob description
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
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
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:
$118,450.00 - $236,900.00
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: 09/27/2026
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.
Sponsorship evidence
Why Openbound reached the conclusions above.
Visa sponsorship evidence
Current posting
Silent on sponsorship
Other openings
15 of 21584 recent openings at this employer state a sponsorship restriction.
Employer H-1B history
- 1,385
- recent certified H-1B filings
- 673
- new-hire petitions
- 0
- filings for similar roles
- 1,296
- so far in FY2026
Filed titles like this role: software development engineer · cloud engineer · mgr software development engineering · software engineer
More evidence details
- 501 certified H-1B filings for closely related roles, though none for this exact title
- 1,385 recent certified H-1B filings across the employer
- Still filing this year — 1,296 filings in FY2026
- 317 USCIS H-1B new-employment approvals, counted separately from LCA filings
- Strong filing activity in AZ
- 2,668 further USCIS approvals for extensions or transfers
- 15 other recent postings at this company state a sponsorship restriction
- The supporting filings are for related work, not for this exact role
- The posting says nothing about sponsorship either way
Strong filing activity in AZ.
Green card sponsorship evidence
Employer PERM history
- 133
- recent certified PERM filings
- 11
- filings for similar roles
- 8
- filings in this location
Filing history reflects past employer behavior; it isn't a promise for this opening.
All open roles at CVS HealthHow Openbound evaluates sponsorship
Visa history uses official U.S. Department of Labor H-1B LCA disclosure data and USCIS H-1B petition history. Green card history uses DOL PERM disclosure data. Each is read for the employer as a whole, for roles like this one, and for this location, weighted toward the most recent fiscal years.
An employer is matched to its filing entities by verified legal name and reviewed aliases; a match is never made on a name resemblance alone. Where no verified entity can be matched, the page says so and draws no conclusion from the absence. 530 filing titles were examined for this employer.
What this posting states outranks history in both directions, and an employer's published policy outranks past filings. Filing history reflects past behavior; it is not a promise of sponsorship for this opening, and none of this is legal advice.