Data Engineer

Join SAIC to build dependable, scalable data pipelines and datasets on the Azure platform. This hybrid role in Washington, DC focuses on hands-on ownership across ingestion, transformation, and delivery, with strong emphasis on governance, security, and performance.

What you’ll do

• Design, develop, schedule, and monitor batch and near real-time data pipelines in Azure Data Factory (ADF) for ingestion, transformation, and ELT/ETL.
• Implement data storage strategies in Azure Blob Storage, including access tiers, lifecycle policies, partitioning, and folder design.
• Design, manage, and optimize datasets in Azure SQL (Database and Managed Instance), covering schema design, indexing, and performance tuning.
• Create and maintain dimensional models (star/snowflake), applying 3NF, normalization/denormalization, and Data Vault 2.0 patterns as appropriate.
• Build data quality and governance capabilities such as validation rules, profiling, lineage, documentation, and standards for schema evolution and data contracts.
• Optimize pipeline runtimes, SQL queries, and storage I/O, including alerting, retry logic, and cost controls to maintain performance and reliability.
• Collaborate with analytics, product, and operations teams to deliver robust, well-documented datasets and data products.
• Apply security and compliance best practices, including RBAC, data masking, encryption at rest/in transit, and key management in line with company policies.
• Contribute reusable components, templates, and best practices to improve consistency and speed across the data platform.

What you’ll bring

• BS and 5 years experience (or 4 years experience in lieu of degree).
• Ability to obtain and maintain a public trust requiring U.S. Citizenship.
• Hands-on experience with Azure Data Factory (ADF): pipelines, data flows, linked services, triggers, and parameterization.
• Strong experience with Azure Blob Storage: containers, access tiers, lifecycle management, SAS, and Managed Identities.
• Strong experience with Azure SQL (Database/Managed Instance): schema design, performance tuning, indexing, and query optimization.
• Practical experience with star and snowflake schemas, 3NF, and Data Vault concepts.
• Understanding of Kimball vs. Inmon data warehousing approaches.
• Proficiency with JSON, Parquet, CSV, Avro plus experience handling schema evolution and versioning for these formats.
• Strong SQL skills for complex querying and transformations.
• Scripting experience in Python (preferred) or Scala for transformations, utilities, and automation.
• Experience with Git-based workflows.
• Experience integrating pipelines with Azure DevOps (Repos, Pipelines) or equivalent CI/CD tooling.
• Proven experience with monitoring, logging, alerting, and troubleshooting data pipelines in production.

Technologies you may work with

• Azure, Azure Data Factory (ADF), Azure Blob Storage, Azure SQL, Azure Synapse Analytics
• Microsoft Fabric, Power BI, Azure Synapse Analytics serverless and/or dedicated SQL pools
• Spark notebooks, Microsoft Fabric Lakehouse, OneLake
• Power BI semantic models, DAX, Azure Functions, Databricks, Spark Structured Streaming
• Event Hubs, Bicep, Terraform, ARM templates, Microsoft Purview
• Python, Scala, JSON, Parquet, CSV, Avro, RBAC, SAS, Managed Identities
• Azure DevOps (Repos, Pipelines), CI/CD, Git
• Power BI incremental refresh, DAX calculation groups

Compensation: USD 140,001 - 180,000 per yearly (typical salary range based on experience and other factors).
Schedule: Full-Time, Day Job
Travel: No
Clearance: Public Trust (must be able to obtain)
Remote Work Potential: ORA_HYBRID
Job ID: 2617790
Category: Information Technology (Big Data Engineer)
Date Posted: 2026-10-09