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Staff Engineer - Salesforce & Data Engineering
CVS Health
Sponsorship not confirmed
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About the job
CVS Health · Galway, IRL · €65,000.00 - €165,000.00 We're building a world of health around every individual , shaping a more connected, convenient and compassionate health experience. The Staff Engineer - Salesforce & Data Engineering reports to the Director of Growth and serves as a technical authority bridging Oak Street Health's Salesforce CRM ecosystem with enterprise-grade cloud data platforms. Key Responsibilities: Lead the architecture, design, and deployment of scalable Azure Databricks data pipelines using PySpark, Delta Live Tables, and Medallion Architecture (Bronze, Silver, Gold layers). Drive enterprise architecture and custom development across the Salesforce platform, including Lightning Web Components (LWC), Visualforce, Apex (Classes, Controllers, Triggers), and Salesforce Flows. Architect and maintain robust enterprise integrations and complex data sync patterns between Salesforce, Azure Data Lake Storage (ADLS), and cloud/on-prem environments. Modernize legacy infrastructure by migrating on-prem SQL pipelines into scalable, cloud-native Databricks solutions using configuration-driven framework patterns (YAML, JSON). Establish DevOps & CI/CD standards across both Salesforce and Data Engineering domains using Infrastructure as Code (IaC) and Pipeline as Code methodologies. Define platform strategy and collaborate with upstream/downstream teams, IT, and BI to drive data quality, eliminate technical debt, and resolve complex architectural bottlenecks. Set technical standards and mentor engineers through rigorous design and code reviews, ensuring platform performance, security, and governance standards are met across teams. Serve as the highest-tier escalation point for complex production issues, pipeline failures, and system performance optimizations. Lead Medicare and payer-focused data initiatives involving member, claims, and operational datasets while ensuring strict PHI/PII compliance and regulatory standards (HIPAA). Create and maintain enterprise-grade documentation for platform architecture, data models, integration standards, and operational procedures. Required Qualifications: 8+ years experience in Software Development, Cloud Technology, or Data Engineering building large-scale platforms. 5–7+ years of hands-on Data Engineering experience with Azure Databricks, Delta Lake, and Azure Data Lake Storage (ADLS). Advanced PySpark development experience, including DataFrames, transformations, joins, aggregations, and performance tuning. Experience developing and maintaining Delta Live Tables (DLT) pipelines. Strong SQL and relational database background (e.g., SOQL, SOSL, MySQL, SQL Server, Oracle) with experience supporting and migrating legacy SQL environments to modern Python/PySpark architectures. Minimum 3+ years working experience with Salesforce custom development (Apex, Visualforce, LWC, web services - SOAP/REST) and Flow automation. Strong understanding of Medallion Architecture (Bronze, Silver, Gold) and building ingestion, transformation, and curation pipelines across all layers. Experience with Infrastructure as Code (IaC), Pipeline as Code, YAML, JSON, and configuration-driven patterns. Experience automating CI/CD deployments using DevOps pipelines across both cloud data and Salesforce environments. Strong quantitative and qualitative analytical abilities with a proven ability to manage multiple priorities. Excellent interpersonal skills and the ability to work across the organization, mentor junior engineers, and foster a positive team environment. Undergraduate degree in Computer Science, Software Engineering, or a related technical field. US work authorization. Some travel required (10%). Preferred Qualifications: Salesforce Certifications (Highly Preferred): Platform Developer II, Integration Architect, or Data Cloud / Data Architecture certifications. Data & Cloud Certifications (Highly Preferred): Databricks Certified Data Engineer (Associate/Professional) or Microsoft Certified: Azure D
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