Data Engineer

SAIC is seeking a hands-on Data Engineer to help design and operate reliable, scalable data pipelines and datasets in a hybrid environment based in Washington, DC. The role emphasizes strong Azure experience, with ownership across ingestion, transformation, governance, and delivery of data products.

This Full-Time position falls under Information Technology and Big Data Engineer work, with a Day Job schedule and No travel requirement. A public trust eligibility is required, with U.S. citizenship needed to obtain and maintain the clearance.

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), including schema design, indexing, and performance tuning.
• Create and maintain dimensional models (star/snowflake), applying 3NF, appropriate normalization/denormalization, and Data Vault 2.0 patterns.
• Implement data quality and governance capabilities, including validation rules, profiling, lineage, documentation, and standards for schema evolution and data contracts.
• Optimize pipeline runtimes, SQL queries, and storage I/O, and 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/in transit, and key management aligned with company policies.
• Contribute best practices, templates, and reusable components to improve consistency and delivery speed across the data platform.

Requirements

• 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, and SAS/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 approaches to data warehousing.
• Proficiency with JSON, Parquet, CSV, and Avro, including experience managing schema evolution and versioning.
• Strong SQL skills for complex querying and transformations.
• Scripting experience in Python (preferred) or Scala for data transformations, utilities, and automation.
• Experience with Git-based workflows.
• Experience integrating data pipelines with Azure DevOps (Repos, Pipelines) or equivalent CI/CD tools.
• Proven experience with monitoring, logging, alerting, and troubleshooting data pipelines in production.

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, Power BI incremental refresh, DAX calculation groups
• 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

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), including 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 ID: 2617790

Location: Washington, DC, US (hybrid; potential for remote work: ORA_HYBRID)

Date Posted: 2026-10-09

Target Salary Range: $140,001 - $180,000 per year