Data Engineer (Remote)

Responsibilities

• Design, build, and maintain automated processes for provisioning data workspaces, including PreProd and Prod environments, with appropriate tools, configurations, and access controls.
• Pre-create standardized workspaces with commonly used analytics, engineering, and visualization tools to streamline onboarding and enhance user experience.
• Implement and manage linked services, mount points, and catalog configuration within Databricks and VA’s VHA Data Lake.
• Support automated data warehouse access provisioning for eligible users, ensuring seamless integration with VA Cloud Data Warehouse (CDW) systems.
• Provide white-glove customer success services, including onboarding sessions, office hours, rapid async support, and creation of reusable templates, guides, and best-practice documentation.
• Collaborate with Customer Success, Business Analysts, and Platform Engineering teams to refine intake processes, improve user satisfaction, and standardize workspace deployment.
• Develop migration guidance and self-service resources to accelerate platform adoption and reduce user friction when transitioning from legacy data systems.
• Troubleshoot user issues related to data access, workspace configuration, pipelines, cataloging, or permissions, escalating to engineering teams when needed.
• Ensure compliance with VA security, governance, and documentation standards while maintaining high system reliability.
• Monitor operational performance, identify bottlenecks, and recommend improvements to workspace automation, data access flows, and user support operations.

Qualifications

• Bachelor’s degree in Information Technology, or a related field (or commensurate experience)
• 12+ years of experience in business analysis, project management, or a similar role
• Strong experience with Databricks and Azure data services, including workspace administration, catalog creation, linked services, storage mounts, and access configuration
• Proficiency in data engineering fundamentals such as ETL/ELT pipeline development, data modeling, and managing structured and unstructured datasets
• Experience with Databricks, including catalog creation, mount configuration, workspace management, and Service Principal setup
• Familiarity with modern data lakehouse architectures, distributed data systems, and cloud data engineering practices
• Ability to automate provisioning workflows and infrastructure using scripting or infrastructure-as-code tools (Python, PowerShell, Bash, Terraform, ARM, or Bicep)
• Skilled in implementing secure identity and access management (IAM), RBAC models, and data governance practices within enterprise or federal environments
• Strong troubleshooting and problem-solving abilities for diagnosing platform, data access, and pipeline issues and collaborating across teams for resolution
• Effective communication skills with the ability to document technical processes, create reusable templates, and support users through onboarding, office hours, and white-glove assistance