Data Engineer

About the role

Build and maintain scalable data pipelines, optimize data solutions, and support analytics and business operations.

Tasks

• Design, develop, and monitor batch and near-real-time data pipelines using Azure Data Factory (ADF).
• Manage Azure Blob Storage, including containers, lifecycle policies, access tiers, and data partitioning.
• Design and optimize Azure SQL databases, including schema design, indexing, and query performance tuning.
• Develop data models using Star Schema, Snowflake Schema, 3NF, and Data Vault 2.0.
• Implement data quality, validation, governance, lineage, and security standards.
• Monitor production pipelines, troubleshoot issues, and improve performance and reliability.
• Apply security best practices, including RBAC, encryption, data masking, and key management.
• Implement reusable components and CI/CD workflows using Git and Azure DevOps.

Requirements

• Minimum 5 years of experience with a bachelor's degree, or 4 years of experience in lieu of a degree.
• Strong hands-on experience with Azure Data Factory, Azure Blob Storage, and Azure SQL.
• Proficiency in SQL, Python or Scala, and data formats such as JSON, Parquet, CSV, and Avro.
• Knowledge of data warehousing methodologies, including Kimball and Inmon.
• Experience with production pipeline monitoring, troubleshooting, and maintenance.
• U.S. citizenship and the ability to obtain and maintain a Public Trust clearance are required.
• Preferred: Experience with Azure Synapse Analytics, Microsoft Fabric, Lakehouse, and OneLake.
• Preferred: Knowledge of Power BI semantic modeling, DAX, and incremental refresh.
• Preferred: Familiarity with Event Hubs, Azure Functions, Databricks, or Spark Structured Streaming.
• Preferred: Experience with Terraform, Bicep, ARM templates, or Microsoft Purview.

Schedule

• Hybrid, 3 Days Onsite Per Week
• W2 / Full-Time

Location

• Washington, DC