Staff Systems Engineer – Digital

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🕒 vor 12 Tagen

⚓ Rhode Island – Remote

⚓ Rhode Island – Remote

💵 $130.295 - $260.590 / Jahr

⏰ Vollzeit

🔴 Experte

⚙️ Systemingenieur

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CVS Health

WebsiteLinkedInAlle Stellen

10.000+ Mitarbeiter

Gegründet 1963

🏥 Gesundheitswesen

⚕️ Krankenversicherung

🛒 Einzelhandel

Healthcare • Healthcare Insurance • Retail

CVS Health ist ein führendes amerikanisches Gesundheitsunternehmen, das sich der Verbesserung des Zugangs zu Gesundheitsdiensten und deren Erschwinglichkeit verschrieben hat. Das Unternehmen verfolgt einen umfassenden Ansatz, der Gesundheitsdienstleistungen, Krankenversicherungen und das Management von Apothekenleistungen umfasst. Durch seine Tochtergesellschaften, wie Aetna und CVS Caremark, bietet CVS Health eine Vielzahl von Dienstleistungen an, die Wohlbefinden, Krankheitsmanagement und erschwinglichen Versicherungsschutz für verschreibungspflichtige Medikamente erleichtern. CVS Health betreibt Apotheken in der Nachbarschaft, bietet Versandapothekendienste an und verwaltet Programme für Spezialmedikamente, um Gesundheitsversorgung für jeden bequem und zugänglich zu machen. Angetrieben von der Mission, Menschen mit wesentlichen Pflegediensten zu verbinden, ist CVS Health bestrebt, gesündere Gemeinschaften zu fördern und das Wohlbefinden aller Menschen zu unterstützen.

Beschreibung

• 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

🎯 Anforderungen

• 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)

🏖️ Vorteile

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