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BlueFlag LLP provides talent and technology services for organizations across B2B, recruitment, and government-related work. Its offerings include talent sourcing through the Human Algorithm™, project and fractional staffing, team assessments, and talent development. BlueFlag also supports project and program management, helping clients staff important initiatives and establish the tools and processes needed to move them forward. The company works with both public- and private-sector organizations, combining staffing expertise with practical delivery support.
Senior Databricks Engineer, ML & Analytics (Remote - United States)
Lead Azure Databricks migrations and delivery for Department of Veterans Affairs workloads across machine learning and analytics. Build governed pipelines, production ML workflows, and reporting solutions for VA teams.
Description
- Partner with Department of Veterans Affairs teams to define use cases, plan migrations, and deliver Databricks solutions
- Evaluate on-premises SQL Server, SSIS, stored procedure, and scheduled-job workloads, then adapt them to Azure Commercial Databricks patterns
- Develop and optimize data pipelines with PySpark, Spark SQL, Delta Lake, Lakeflow, and Azure Data Factory
- Govern customer data with Unity Catalog access controls, lineage, and sharing capabilities
- Enable customer adoption through workshops, paired delivery, and practical documentation
- Create reusable templates and code with Git, CI/CD, and Databricks Asset Bundles
- Develop complete ML workflows covering feature engineering, model training, evaluation, MLflow tracking, Unity Catalog model registration, and serving
- Help data scientists deploy models into governed and monitored production environments
- Support generative AI initiatives, including retrieval-augmented generation and agent-based solutions
- Migrate SSIS and stored-procedure ETL into reconciled Databricks pipelines
- Modernize on-premises reporting with Databricks SQL, AI/BI dashboards, and Power BI
- Publish reporting datasets from Databricks SQL warehouses, including semantic models and query-performance optimization
Requirements
- Bring at least 7 years of data engineering experience, including 2 or more years delivering production Databricks workloads
- Demonstrate strong Python, SQL, PySpark, and Spark SQL skills
- Have hands-on expertise with Delta Lake, medallion lakehouse architecture, and Spark performance optimization
- Have practical Unity Catalog experience with catalogs, grants, lineage, and row- and column-level security
- Have migrated on-premises systems such as SQL Server, SSIS, and stored procedures to cloud platforms
- Know Azure services including ADLS Gen2, Azure Data Factory, Entra ID, and Key Vault
- Use Git, CI/CD, and infrastructure-as-code tools such as Databricks Asset Bundles and Terraform
- Bring customer-facing consulting or professional services experience involving requirements sessions, workshops, and training
- Communicate clearly with both technical and non-technical stakeholders in writing and conversation
- Hold a bachelor's degree in computer science, information systems, or a related discipline
- Be a United States citizen
- Be able to obtain a public trust clearance
- Be eligible to work in the United States
- For the AI/ML focus, have experience training, evaluating, and deploying models with MLflow and frameworks such as scikit-learn, XGBoost, or PyTorch
- For the analytics focus, understand Databricks SQL and Power BI data modeling, including star schemas, semantic models, and DAX
- Preferred qualifications include Databricks certifications, healthcare data and HIPAA experience, Azure Government or FedRAMP High experience, Hive metastore to Unity Catalog upgrades, Mosaic AI Vector Search, Agent Framework or model monitoring experience, and familiarity with Microsoft Fabric, Pyramid Analytics, or Genie
Benefits
- Competitive compensation package
- Generous annual leave and paid holiday time
- Comprehensive group medical and dental coverage
- 401(k) plan with employer matching
- Life insurance and accidental death and dismemberment coverage
- Continuing education and professional development opportunities
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