Position Type: Direct Hire / Full-Time
Location: Arlington, VA / Washington, DC Metro Area - Hybrid Onsite work locations include Rosslyn, the Mark Center, and the Pentagon.
Clearance: Secret Clearance Preferred
Hiring Timeline: Immediate
Compensation:
- Junior Data Integration Engineer: Approximately 2+ years of relevant experience | $60,000-$100,000/year
- Senior Data Integration Engineer: 10+ years of relevant experience | $95,000-$135,000/year
Company: The name of our partner organization will be disclosed during the interview process. This is not a direct role with LaunchCode; it is a position through LaunchCode, working with one of our partner companies.
Position Overview:
Our partner is seeking Data Integration Engineers at the Junior and Senior levels to support enterprise data integration, financial systems, cloud data platforms, and modernization initiatives for Defense sector clients. Engineers will help design, develop, validate, test, and support data integrations across financial systems, ERP platforms, staging environments, analytics platforms, and reporting solutions. The team works closely with technical developers, source system owners, data engineering teams, finance stakeholders, and program management to ensure data moves accurately, securely, and reliably from source systems through transformation pipelines to downstream reporting platforms.
This role provides exposure to technologies including OneStream, ERP platforms, GTAS reporting, War Data Platform, Power BI, Databricks, Palantir, Celonis Intelligence, SQL, Python, cloud-based integration services, and AI-enabled data solutions.
Position Responsibilities:
- Design, develop, configure, test, and support enterprise data integrations.
- Support integrations involving OneStream, ERP platforms, financial systems, analytics platforms, and reporting solutions.
- Develop and support APIs, ETL/ELT pipelines, batch integrations, file transfers, and cloud-based data movement processes.
- Support source-to-target mapping, transformation logic, interface controls, and validation requirements.
- Validate data movement across source systems, staging environments, transformation layers, and downstream reporting platforms.
- Perform data validation and reconciliation to identify discrepancies and ensure data accuracy, completeness, and traceability.
- Troubleshoot interface failures, mapping issues, schema changes, rejected records, transformation errors, and other data processing exceptions.
- Support System Integration Testing (SIT), User Acceptance Testing (UAT), production deployments, cutovers, and post-production stabilization.
- Collaborate with software developers, data engineers, finance teams, source system owners, and business stakeholders.
- Create and maintain technical documentation, interface specifications, mapping documents, reconciliation procedures, and operational runbooks.
- Support enterprise modernization initiatives, system implementations, data conversions, and production cutovers.
- Monitor production interfaces and identify opportunities to improve automation, performance, scalability, and reliability.
- Use SQL, Python, Power BI, Databricks, Palantir, and other technologies to analyze data and support data quality initiatives.
- Leverage AI-assisted tools and emerging technologies to improve data validation, reconciliation, anomaly detection, and operational support.
Junior Level - Required Skills/Experience:
- Approximately 2+ years of experience in data engineering, data integration, software engineering, ETL development, API development, or a related technical field.
- Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Engineering, Computer Engineering, Information Technology, or another STEM discipline.
- U.S. citizenship and ability to obtain and maintain a Secret clearance.
- Experience with SQL and relational databases.
- Familiarity with ETL/ELT pipelines, APIs, batch processing, file-based integrations, or data movement processes.
- Exposure to data mapping, transformation logic, data validation, or reconciliation.
- Experience troubleshooting technical issues and analyzing data discrepancies.
- Familiarity with cloud-based data platforms such as Azure, AWS, or Databricks.
- Strong analytical and problem-solving skills.
- Ability to communicate effectively and collaborate with technical and business teams.
Senior Level - Required Skills/Experience:
- 10+ years of experience supporting enterprise data integration, financial systems, ERP modernization, cloud data engineering, or related initiatives.
- Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Engineering, Computer Engineering, Information Technology, or another STEM discipline.
- U.S. citizenship and active Secret clearance preferred. The company is willing to sponsor the right candidate.
- Strong experience developing or supporting APIs, ETL/ELT pipelines, batch processing, file-based integrations, or middleware platforms.
- Advanced SQL skills with experience querying, validating, and reconciling large datasets.
- Strong experience with source-to-target validation, data reconciliation, and enterprise data quality.
- Experience supporting SIT, UAT, production deployments, cutovers, and post-production support.
- Strong understanding of enterprise integration patterns, data mapping, transformation logic, and interface controls.
- Experience with cloud-based data platforms such as Azure, AWS, or Databricks.
- Strong troubleshooting, root-cause analysis, and technical problem-solving skills.
- Excellent communication skills and the ability to work directly with technical teams, business stakeholders, and leadership.
- Ability to manage multiple priorities in a fast-paced consulting environment.
Preferred Qualifications - Junior & Senior:
- Experience with OneStream or other Enterprise Performance Management (EPM) platforms.
- Experience with ERP systems such as SAP, Oracle, Workday, Momentum, or CGI Momentum.
- Knowledge of federal financial management, GTAS, USSGL, Treasury reporting, financial statements, audit readiness, or internal controls.
- Experience supporting Advana, War Data Platform, or other federal enterprise data platforms.
- Experience with REST APIs, Azure Data Factory, Azure Integration Services, Informatica, MuleSoft, Boomi, Kafka, or similar technologies.
- Experience with Databricks, Spark, Delta Lake, Microsoft Fabric, Synapse Analytics, or similar cloud data architectures.
- Knowledge of data governance, metadata management, master data management (MDM), and enterprise data quality.
- Experience applying AI, intelligent automation, or agentic AI to data validation, reconciliation, anomaly detection, or interface monitoring.
- Relevant professional certifications such as Microsoft Azure Data Engineer Associate, Databricks Data Engineer Associate, AWS Certified Data Engineer, Certified Scrum Master (CSM), or Certified Data Management Professional (CDMP).
- Candidates with backgrounds in Software Engineering, Cloud Engineering, Data Engineering, API Development, Middleware Engineering, ETL Engineering, or ERP Integration are encouraged to apply.