> Markdown version of [/jobs/ext/3095784-senior-data-engineer-enterprise-modernization](https://www.wearedevelopers.com/jobs/ext/3095784-senior-data-engineer-enterprise-modernization). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer, Enterprise Modernization - **Company:** FI Consulting - **Location:** Arlington, VA, United States - **Experience:** Expert - **Salary:** $150,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Application Services, Microsoft Azure, Business Systems, Configuration Management, Code Review, Information Systems, Databases, Data as a Services, Data Architecture, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Profiling, Data Security, Data Structures, Data Stores, Data Systems, Relational Databases, Python (Programming Language), PostgreSQL, Machine Learning, Meta-Data Management, Metadata Repositories, Microsoft SQL Server, Operational Data Store, OpenShift, Oracle (Applications), Scrum Methodology, Search Technologies, Software Engineering, Systems Integration, Talend, Unstructured Data, Web Services, Enterprise Data Management, Data Logging, Data Processing, Google Cloud, Data Ingestion, Azure Data Factory, Informatica Powercenter, Retrieval-Augmented Generation, Git, Kubernetes, Information Technology, Data Lineage, Deployment Automation, AWS Glue, Integration Frameworks, Bitbucket, Data Management, Api Design, Restful APIs, Software Version Control, Data Pipelines, Docker - **Published:** September 26, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18445399?backUrl=%2Fcareer%2F18445399%2FSenior-Data-Engineer-Enterprise-Modernization-Virginia-Arlington ## About the Role * Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Applied Mathematics, or a related technical field. * 8-15+ years of experience in data engineering, systems integration, ETL/ELT development, software engineering, or enterprise data management. * Experience designing and implementing enterprise data pipelines and reusable data integration solutions. * Experience working in modern engineering environments using source control (Git/Bitbucket) and CI/CD pipelines for collaborative development and automated deployment. * Strong SQL development, relational database design, and query-optimization experience. * Proficiency with Python and experience applying modern software engineering practices to data-processing solutions. * Experience developing and consuming RESTful APIs, web services, database interfaces, and file-based integrations. * Experience integrating structured and unstructured data from multiple source systems. * Experience creating source-to-target mappings, transformation specifications, interface documentation, and data lineage. * Experience implementing automated data quality, validation, reconciliation, logging, and monitoring controls. * Ability to translate business and data requirements into secure, maintainable technical solutions. * Experience working in Agile delivery environments and collaborating across technical and functional teams. * Strong analytical, troubleshooting, written communication, and technical documentation skills. * Ability to obtain and maintain a Top Secret clearance. * Must be available to work onsite in Washington, DC upon project start., * Experience supporting federal government clients and multi-agency data initiatives. * Experience integrating federal grants, financial management, acquisition, performance management, or operational data. * Experience with PostgreSQL, SQL Server, Oracle, or comparable enterprise database platforms. * Experience with data orchestration or integration tools such as Apache Airflow, Azure Data Factory, AWS Glue, Informatica, Talend, or comparable technologies. * Experience with cloud or hybrid data services in Azure, AWS, or Google Cloud. * Experience deploying containerized data-processing solutions using Docker, Kubernetes, or OpenShift. * Familiarity with data governance, metadata management, master data management, and data catalog solutions. * Experience implementing data lineage, provenance, source traceability, and auditability capabilities. * Experience preparing data for advanced analytics, semantic search, retrieval-augmented generation, or machine learning applications. * Experience supporting financial management, accounting, budgeting, grants management, reconciliation, or reporting environments. ## Description FI Consulting is seeking a Senior Data Engineer to support a federal government data modernization initiative focused on integrating and analyzing enterprise grants, financial, performance, and operational data. The Senior Data Engineer serves as a hands-on technical leader responsible for designing and implementing reusable data ingestion frameworks, enterprise integrations, and scalable data pipelines. The role works closely with data architects, business stakeholders, analytics specialists, application developers, and security personnel to integrate disparate data sources and create a trusted, centralized data environment. The ideal candidate has 8 or more years of experience leading data integration efforts, developing enterprise ETL/ELT solutions, building API-based integrations, and implementing data quality controls in complex federal or enterprise environments. Responsibilities * Design, develop, and maintain scalable enterprise data pipelines, ingestion frameworks, and integration services. * Lead the development of reusable connectors and automated data acquisition processes across multiple agency systems and environments. * Design and implement ETL/ELT solutions that support structured and unstructured data sources. * Integrate data from grants, financial, operational, performance, and business systems using APIs, files, relational databases, and approved platform services. * Collaborate with the Lead Data Architect and Solution Architect to implement canonical data models, integration patterns, and engineering standards. * Develop and maintain source-to-target mappings, transformation rules, interface specifications, data lineage, and technical documentation. * Implement data profiling, validation, reconciliation, monitoring, and data quality controls. * Apply secure data-handling practices, including protection of PII and sensitive financial data through appropriate encryption in transit and at rest, access controls, and safeguarding of data throughout the pipeline. * Optimize data processing workflows for performance, scalability, reliability, maintainability, and repeatability. * Support centralized data repositories and analytics-ready data structures used for reporting, search, analysis, and application services. * Troubleshoot complex integration, pipeline, and data quality issues and perform root-cause analysis. * Collaborate with analytics and application teams to prepare governed, traceable data for semantic search, dashboards, analytical signals, and reporting. * Participate in backlog refinement, sprint planning, daily coordination, demonstrations, technical reviews, and retrospectives. * Mentor data engineers, conduct code reviews, and establish reusable engineering practices. * Ensure data solutions follow applicable security, privacy, governance, records-management, and configuration-management requirements. * Support deployment, testing, documentation, knowledge transfer, and transition activities across development, test, staging, and production environments. ## Related Videos - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Best Paying Jobs in Technology](https://www.wearedevelopers.com/magazine/256-best-paying-jobs-in-technology)