Data Engineer

SAIC is seeking a hands-on Data Engineer to build and maintain reliable, scalable data pipelines and datasets. This hybrid role in Washington, DC focuses on ingestion, transformation, and data product delivery across Azure data services, with an emphasis on governance, security, and performance.

Responsibilities

• Design, develop, schedule, and monitor batch and near real-time data pipelines in Azure Data Factory (ADF) for ingestion, transformation, and load (ELT/ETL).
• Implement and manage 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/Managed Instance), covering schema design, indexing, and performance tuning.
• Create and maintain dimensional models using star/snowflake patterns, applying 3NF, normalization/denormalization, and Data Vault 2.0 where appropriate.
• Implement data quality and governance capabilities, including validation rules, profiling, lineage, documentation, and standards for schema evolution and data contracts.
• Optimize pipeline runtime, SQL queries, and storage I/O; implement alerting, retry logic, and cost controls to support 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 and in transit, and key management aligned with company policies.
• Contribute to reusable templates and best practices to improve consistency and delivery speed across the data platform.

Requirements

• BS plus 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), including pipelines, data flows, linked services, triggers, and parameterization.
• Strong experience with Azure Blob Storage, including containers, access tiers, lifecycle management, and SAS/Managed Identities.
• Strong experience with Azure SQL (Database/Managed Instance), including 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, including 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 data pipelines with Azure DevOps (Repos, Pipelines) or equivalent CI/CD tools.
• Proven production experience with monitoring, logging, alerting, and troubleshooting for data pipelines.

Technologies

• 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

Desired

• Experience with Azure Synapse Analytics: serverless and/or dedicated SQL pools, data warehouse patterns, and Spark notebooks for large-scale ELT/ETL.
• Familiarity with Microsoft Fabric: Lakehouse, OneLake, notebooks, data pipelines, and workspace governance.
• Experience building Power BI semantic models (datasets), incremental refresh, relationships, calculation groups, and DAX for data product delivery.
• Experience with Event Hubs, Azure Functions, or Databricks/Spark Structured Streaming for real-time or near real-time ingestion.
• Experience using Bicep or Terraform to provision and manage Azure resources, including familiarity with ARM templates.
• Experience with Microsoft Purview or similar tools for data cataloging, lineage, and metadata management.

Job Details

• Job ID: 2617790
• Location: Washington, DC, US
• Posting date: 2026-10-09
• Category: Information Technology
• Subcategory: Big Data Engineer
• Schedule: Full-Time
• Shift: Day Job
• Travel: No
• Potential for remote work: ORA_HYBRID
• Minimum clearance required: None
• Clearance level must be able to obtain: Public Trust

Compensation

USD 140,001 - 180,000 per year. The estimate displayed represents the typical salary range for this position based on experience and other factors.