Infopact is seeking an experienced Data Engineer to support large-scale Department of Defense data and financial management initiatives. The ideal candidate will have hands-on experience developing and optimizing data pipelines using Databricks and Advana / the War Data Platform, with strong expertise in Python, PySpark, and SQL.

This role will work with complex Federal Financial Management and General Ledger datasets to build scalable data pipelines, improve data quality, support reconciliation and analytics, and deliver trusted data products for mission and financial-management stakeholders.

• Design, develop, maintain, and optimize scalable data pipelines within Databricks and Advana / the War Data Platform.
• Build and manage ETL/ELT workflows for ingesting, cleansing, transforming, aggregating, and integrating large-scale datasets.
• Develop Databricks solutions using Delta Lake, Autoloader, PySpark, SQL, and job scheduling/workflows.
• Implement data architectures following the Medallion Architecture (Bronze, Silver, and Gold layers).
• Process and analyze large-scale Federal Financial Management and General Ledger (GL) datasets.
• Support Universe of Transactions (UoT) reconciliations, data traceability, and financial data validation.
• Design and implement data-quality frameworks, automated validation checks, reconciliation controls, and exception handling.
• Develop solutions within AWS GovCloud, including integration with services such as Amazon S3.
• Troubleshoot pipeline failures, identify performance bottlenecks, and optimize data-processing workloads.
• Support CI/CD processes and source-code management using GitLab or comparable technologies.
• Collaborate with data analysts, product owners, financial-management SMEs, and Government stakeholders to translate business requirements into reliable data solutions.
• Develop technical documentation covering data pipelines, transformations, business rules, data lineage, and operational procedures.

• Demonstrated experience building, managing, and optimizing data pipelines using Databricks.
• Experience working within Advana / the War Data Platform.
• Advanced proficiency in Python, particularly PySpark and Pandas.
• Expert-level SQL skills, including complex queries, transformations, joins, aggregations, and performance optimization.
• Hands-on experience with Delta Lake, Autoloader, and Databricks job scheduling/workflows.
• Strong experience designing and implementing ETL/ELT processes and data-wrangling solutions.
• Experience working with large-scale Federal Financial Management and General Ledger data.
• Knowledge of Universe of Transactions (UoT) reconciliation concepts and processes.
• Experience working in AWS GovCloud, including S3.
• Familiarity with Bronze/Silver/Gold Medallion data architecture.
• Experience implementing automated data-quality and validation frameworks.
• Understanding of CI/CD principles and experience with GitLab or similar version-control platforms.
• Strong analytical, troubleshooting, and problem-solving skills.
• Strong written and verbal communication skills.

• Experience with Databricks Unity Catalog, including data governance, access controls, lineage, and metadata management.
• Knowledge of SAP data structures and financial data.
• Prior experience supporting DoD financial management, audit, ERP, or enterprise data initiatives.
• Experience integrating financial and ERP data from multiple authoritative data sources.
• Familiarity with financial auditability, reconciliation, data lineage, and traceability requirements.

Candidates must possess an active Interim Secret clearance or higher and maintain the required clearance throughout employment.

Infopact, Inc. is a federal technology and professional services company supporting government customers with data and analytics, enterprise financial management, ERP, cloud modernization, automation, and emerging technologies. We deliver mission-focused solutions that help agencies transform complex enterprise data into trusted, actionable information.

Infopact, Inc. is an Equal Opportunity Employer.