Data Quality Engineer (Remote)

• Define appropriate measures to ensure data quality.
• Analyzes and assesses existing source system data to design appropriate data-centric solutions.
• Participate in all aspects of testing, including functional, regression, load and system testing.
• Troubleshoot user issues related to data access, workspace configuration, pipelines, cataloging, or permissions, escalating to engineering teams when needed.
• Support 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.
• Monitor operational performance, identify bottlenecks, and recommend improvements to workspace automation, data access flows, and user support operations.

• 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.
• 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.

Preferred Skills and Experience:

• Certified Data Management Professional
• Familiarity with modern data lakehouse architectures, distributed data systems, and cloud data engineering practices.
• Strong understanding of Azure data services, including storage, compute, identity and access management, and DevOps workflows.
• Experience with workflow automation, CI/CD pipelines, or infrastructure-as-code (e.g., Terraform, ARM, Bicep).
• Background in user-facing or customer-success-adjacent work such as onboarding, training, communications, or technical support.
• Knowledge of enterprise data systems common to healthcare or federal environments, especially data governance and data-security considerations.
• Experience with tools such as Jira, ServiceNow, or SharePoint for intake, change management, and support processes.
• Strong communication skills with the ability to create clear guides, templates, intake documentation, and best-practice recommendations.

Clearance Required

• Ability to obtain and maintain a suitability/Public Trust

USD $175,000.00 - USD $195,000.00 /Yr.