Jobs in United States

Staff Systems Engineer in Work At Home Arizona

1 active opportunities · Updated October 2026

Explore current staff systems engineer jobs in Work At Home Arizona. Filter by work mode, employment type, experience, department, date posted and distance.

Hiring demand

28/100

cooling · 6 related jobs

Hiring trend

-50%

Job postings compared with the previous 30 days

Remote options

66.7%

Share of matching jobs listed as remote

C
📍 Work At Home Arizona, United States
✓ High-confidence listingDemand 28/100Company trend +340.2%
Quick readStrong listing-quality and freshness signals

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 acro

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