Databricks SME (Remote)

Govcio LLC•UNAVAILABLE, UNAVAILABLE

9d•Remote

About The Position

GovCIO is hiring a Databricks SME to support the Department of Veterans Affairs (VA) Data Modernization initiative. In this role, the Databricks SME will guide data scientists, analysts, infrastructure specialists and business SME to deliver production-ready data solutions. This position focuses on workspace automation, onboarding support, data platform usability, infrastructure provisioning, and white‑glove customer success to ensure VA users can rapidly adopt and leverage modern data tools. This position is fully remote within the United States.

Requirements

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.
Ability to automate provisioning workflows and infrastructure using scripting or infrastructure‑as‑code tools (Python, PowerShell, Bash, Terraform, ARM, or Bicep).
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.

Nice To Haves

Experience with Data Analysis, Data Curation, Data Visualization (PowerBi), Python, Azure Synapse/Azure Data Factory, Azure Data Lake Storage, SQL Server.
Certifications: Azure Databricks and Spark for Data Engineers, PySpark and SQL, Microsoft Azure Cert, SQL, SQLlite, Python Pandas, Sybase/SAP PowerDesigner, Databricks DAB, Databricks Unity Catalog, and Databricks lakflow pipelines
Exposure to Starburst, PowerBI, SSRS, SSIS and Unity Catalog
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.
Ability to translate business needs into technical requirements and develop scalable solutions that improve platform efficiency.
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.
Ability to obtain and maintain a suitability/Public Trust

Responsibilities

Implement and manage linked services, mount points, and catalog configuration within Databricks and VA’s VHA Data Lake.
Develop and optimize PySpark (Python/Scala) jobs, notebooks, and workflows in Databricks.
Build ETL/ELT pipelines using Azure Databricks Lakehouse features.
Design and implement Spark-based data processing for analytics workloads.
Optimize Databricks Spark jobs for performance, cost, and scalability (partitioning, caching, tuning, etc.).
Collaborate with data scientists, analysts, infrastructure specialists and business SME to deliver production-ready data solutions.
Ensure data quality, governance, and security best practices.
Act as subject matter experts to the workgroups from start to finish in their migration to the cloud.
Help workgroups set up their resources and migrate their work loads.
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.