Azure Data Engineer: Scalable Pipelines & Data Platforms

Saic; Washington (District of Columbia); On-site; USD 140,000 - 180,000; Full time

Job summary

SAIC seeks a hands-on Data Engineer with strong Azure experience to build and maintain reliable data pipelines and datasets powering analytics and operational insights. You will own ingestion, transformation, and data product delivery across Azure services, with core use of ADF, Blob Storage, and Azure SQL.

You will design, develop, and operate data solutions using multiple modeling approaches (star/snowflake, Data Vault) and formats (JSON, Parquet, CSV, Avro), collaborating with analytics,

Qualifications

• BS and 5 years experience (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, parameterization.
• Strong experience with Azure Blob Storage: containers, access tiers, lifecycle management, SAS/Managed Identities.
• Strong experience with Azure SQL (Database/Managed Instance): schema design, performance tuning, indexing, 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.
• Experience handlingschema evolution and versioning for these formats.
• 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 environments.

Responsibilities

• Design, develop, schedule, and monitor batch and near real-time data pipelines in Azure Data Factory (ADF) for data ingestion, transformation, and load (ELT/ETL).
• Implement and manage data storage strategies in Azure Blob Storage (access tiers, lifecycle policies, partitioning, 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), and apply 3NF, normalization/denormalization, and Data Vault 2.0 patterns where appropriate.
• 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; implement alerting, retry logic, and cost controls to ensure performance and reliability.
• Collaborate with analytics, product, and operations teams to understand requirements and 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 to best practices, templates, and reusable components to improve consistency and speed of delivery across the data platform.

Skills

Azure Data Factory

SQL

Python/Scala

Data modeling

Data governance

Education

BS degree (or 4 years in lieu of degree)

Tools

Azure Blob Storage

Azure SQL

Azure Synapse Analytics

Microsoft Fabric

Power BI

Git-based workflows

Azure DevOps

Job description

SAIC seeks a hands-on Data Engineer with strong Azure experience to build and maintain reliable data pipelines and datasets powering analytics and operational insights. You will own ingestion, transformation, and data product delivery across Azure services, with core use of ADF, Blob Storage, and Azure SQL.

You will design, develop, and operate data solutions using multiple modeling approaches (star/snowflake, Data Vault) and formats (JSON, Parquet, CSV, Avro), collaborating with analytics,