Location: Remote
Clearance Level: Active Secret
Rackner is seeking a Data Engineer to design, develop, and maintain data ingestion, transformation, integration, and data quality processes supporting modern cloud-based data platforms.
The Data Engineer will work primarily within the Microsoft Fabric environment, developing scalable data pipelines and implementing Bronze, Silver, and Gold medallion architecture layers across assigned data domains. This role will support the ingestion and transformation of data from student information systems, HR/personnel systems, financial systems, operational databases, and other enterprise data sources.
The Data Engineer will also support education data integration using the Ed-Fi Data Standard and REST APIs, including source-to-Ed-Fi mapping, descriptor customization, synchronization, validation, and future migration activities.
Responsibilities- Develop and maintain data ingestion pipelines, transformation logic, and data quality processes within Microsoft Fabric
- Implement and maintain Bronze, Silver, and Gold medallion architecture layers for assigned data domains
- Extract, transform, and load data from enterprise source systems, including:
- Student information systems
- HR and personnel systems
- Financial systems
- Logistics systems
- IT service management platforms
- Operational databases
- Develop ETL and ELT pipelines that ingest source-system data into the Microsoft Fabric Lakehouse
- Build and maintain data integration pipelines, API connections, and automated synchronization processes
- Develop Ed-Fi REST API integrations supporting education data workstreams
- Implement Aspen-to-Ed-Fi export mappings, descriptor customization, transformation logic, and API-based data synchronization
- Develop non-education data ingestion pipelines supporting HR/DCPDS, finance, logistics, and IT service management domains
- Perform source-system data profiling, mapping, cleansing, and transformation
- Conduct reconciliation testing and validate data completeness, accuracy, and consistency across source and target systems
- Identify, troubleshoot, and resolve data quality, pipeline, and integration issues
- Develop SQL queries, Python or PySpark processing logic, and reusable data transformation components
- Support data population and migration activities across cloud and enterprise data environments
- Produce and maintain technical documentation for data pipelines, interfaces, mappings, transformation logic, and operational processes
- Collaborate with data architects, analysts, governance specialists, application teams, and source-system owners to define and implement data integration requirements
- Support Ed-Fi Data Management Service (DMS) migration planning as the DMS reaches production readiness
- Support knowledge transfer and operational transition activities for implemented pipelines and data services
- Experience developing data pipelines, ETL/ELT processes, and data integrations
- Experience with Microsoft Fabric, Azure Data Factory, or comparable cloud data platforms
- Strong SQL proficiency, including querying, transformation, validation, and troubleshooting
- Experience with Python and/or PySpark for data engineering workloads
- Experience working with structured and semi-structured enterprise data
- Understanding of cloud-based data lake, lakehouse, or data warehouse architectures
- Experience with data mapping, data profiling, reconciliation testing, and data quality processes
- Experience integrating systems through REST APIs or similar application interfaces
- Ability to document data flows, pipeline configurations, mappings, and technical processes
- Strong troubleshooting, analytical, and communication skills
- Active Secret clearance
- Experience with Microsoft Fabric Lakehouse architecture
- Experience implementing Bronze, Silver, and Gold medallion data architectures
- Experience with the Ed-Fi Data Standard, Ed-Fi ODS/API, or Ed-Fi REST APIs
- Experience performing Aspen-to-Ed-Fi mapping or integrating other student information systems with Ed-Fi
- Experience with HR/DCPDS, financial, logistics, or IT service management data
- Experience supporting large-scale cloud data migrations or modernization initiatives
- Familiarity with data governance, metadata management, lineage, and enterprise data quality practices
About Rackner
Rackner is a software consultancy focused on building mission-critical systems for the U.S. government. Our teams work across cloud platforms, DevSecOps, AI/ML, distributed systems, and modern software engineering initiatives supporting federal agencies and national security missions. Rackner engineers and technical teams collaborate closely with leadership, program teams, and mission stakeholders to design, demonstrate, and improve software systems that address complex operational challenges.
Benefits & Perks
At Rackner, we believe that when our people grow, our company grows with them, and we are committed to supporting their growth, development and success. We are proud to offer a creative and forward-thinking environment that includes:
• Company-supported certifications aligned to current and future program work,
including cloud, Kubernetes, DevSecOps, security, AI/ML, project management, and
related technical areas
• Clear advancement tracks and future leadership opportunities
• 401(k) with 100% match up to 6%
• Comprehensive medical, dental, vision, life, and disability coverage
• Generous PTO and paid holidays
• Home-office equipment plan and remote work support
• Fitness and wellness reimbursement
• Weekly pay schedule and modern perks, including team events
Equal Opportunity
Rackner is an equal opportunity employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other protected characteristics.
Skills Required
- Experience developing data pipelines, ETL/ELT processes, and data integrations
- Experience with Microsoft Fabric, Azure Data Factory, or comparable cloud data platforms
- Strong SQL proficiency for querying, transformation, validation, and troubleshooting
- Experience with Python and/or PySpark for data engineering workloads
- Experience working with structured and semi-structured enterprise data
- Understanding of cloud-based data lake, lakehouse, or data warehouse architectures
- Experience with data mapping, profiling, reconciliation testing, and data quality processes
- Experience integrating systems through REST APIs or similar application interfaces
- Ability to document data flows, pipeline configurations, mappings, and technical processes
- Strong troubleshooting, analytical, and communication skills
- Active Secret clearance
- Experience with Microsoft Fabric Lakehouse architecture
- Experience implementing Bronze, Silver, and Gold medallion data architectures
- Experience with the Ed-Fi Data Standard, Ed-Fi ODS/API, or Ed-Fi REST APIs
- Experience performing Aspen-to-Ed-Fi mapping or integrating student information systems with Ed-Fi
- Experience with HR/DCPDS, financial, logistics, or IT service management data
- Experience supporting large-scale cloud data migrations or modernization initiatives
- Familiarity with data governance, metadata management, lineage, and enterprise data quality practices
What We Do
Rackner builds cutting-edge solutions that apply DevSecOps and the power of AI in the datacenter, public and private clouds, and edge, leveraging the future of compute capability and technologies like Kubernetes (k8s) and WebAssembly (WASM). We're a member of the Cloud Native Computing Foundation and a Kubernetes Certified Service Provider - as well as a partner to the major public cloud companies. Our customers include hypergrowth startups and federal agencies, both Civilian and Defense. Core Competencies - DevSecOps - Edge Computing - AI/ML - Cloud-Native and Hybrid-Cloud development - Web and Mobile Applications Development (Microservices)









