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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Integration Engineer - **Company:** Miami Nation Enterprises - **Location:** Reston, VA, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Geographic Information Systems, Application Programming Interfaces (APIs), Business Analytics Applications, Build Automation, BigQuery, Cloud Computing, Cloud Database, Cloud Storage, Information Systems, Databases, Data Deduplication, Information Engineering, Data Integration, Data Mapping, Data Security, Data Sharing, Data Warehousing, Relational Databases, Database Queries, Data Flow Control, Github, Python (Programming Language), OAuth, Scrum Methodology, Queueing Systems, Release Management, Cloud Services, Software Engineering, SQL Databases, Data Streaming, Systems Integration, Test Data, Data Logging, Google Cloud, Delivery Pipeline, Grafana, Appian, Git, Event Driven Architecture, Infrastructure Automation Frameworks, Information Technology, Low-code, Data Management, Api Design, Restful APIs, Webhooks, Data Pipelines, Docker - **Published:** October 8, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=744e5e96eb3f3c6e ## About the Role * Minimum four years of professional experience in data engineering, systems integration, software engineering, or a related technical role. * Experience designing and implementing REST APIs, data pipelines, system interfaces, or integration services. * Strong SQL skills and experience working with relational databases and structured data models. * Proficiency with Python, Java, or another language commonly used for data and integration services. * Experience with schema design, data mapping, transformations, validation, reconciliation, and error handling. * Experience deploying and supporting workloads in a cloud environment. * Experience with Git or GitHub, peer review, automated builds, testing, and deployment pipelines. * Ability to troubleshoot issues across applications, APIs, databases, networks, credentials, and cloud services. * Strong written and verbal communication skills and the ability to work with technical and nontechnical stakeholders. * Bachelor's degree in computer science, information systems, data engineering, or a related field, or equivalent practical experience., * Experience with Google Cloud Platform services such as BigQuery, Cloud Run, Cloud Functions, Pub Sub, Cloud Storage, or Dataflow. * Experience with event-driven architecture, message queues, webhooks, and asynchronous processing. * Experience with data warehouses, analytics platforms, geospatial data, or environmental information systems. * Experience securing APIs and service-to-service integrations using OAuth, service accounts, certificates, or comparable controls. * Experience with Docker, infrastructure as code, observability tools, and automated data-quality testing. * Experience integrating Appian or another low-code platform with external services and databases. * Familiarity with federal security, accessibility, records management, and production release requirements., Successful candidates must be able to pass a government background investigation and satisfy public trust requirements. US Citizenship or US Green Card is required. ## Description The successful candidate will work with federal stakeholders, solution architects, application developers, business analysts, quality assurance engineers, and data owners. The role requires strong experience with APIs, data pipelines, SQL, cloud data services, and integration troubleshooting, along with the ability to turn evolving requirements into secure, maintainable interfaces and operational support procedures., * Design and implement data exchanges among applications, databases, APIs, and supporting cloud services. * Develop and maintain batch, event-driven, and API-based integration components appropriate to each use case. * Translate interface requirements and source-to-target mappings into schemas, transformations, validation rules, and error-handling logic. * Develop reusable services and pipeline components that support secure data ingestion, transformation, distribution, and reconciliation. * Implement logging, correlation identifiers, retry handling, failure queues, and other controls needed to diagnose and recover failed transactions. * Participate in architecture reviews and document interface designs, dependencies, data flows, and deployment requirements. Data Engineering and Quality * Profile source data and identify quality, completeness, consistency, and ownership issues that affect integration behavior. * Develop SQL and automated checks that validate schemas, record counts, key relationships, field values, and transformation outcomes. * Support data mapping, normalization, deduplication, reference-data management, and reconciliation across systems. * Work with quality assurance engineers to create representative test data and automate integration and data-quality tests. * Support migration rehearsals, cutover planning, rollback procedures, and post-deployment validation when integrations move data between systems. Cloud Operations and Delivery * Build and support integration workloads using Google Cloud Platform or comparable cloud services. * Create deployment pipelines and infrastructure configurations that promote consistent delivery across development, test, staging, and production environments. * Monitor pipeline health, throughput, latency, failures, and data-quality indicators and respond to operational issues. * Manage source code, configuration, and peer review through Git or GitHub workflows. * Document runbooks, support procedures, known limitations, recovery steps, and operational ownership. * Participate in sprint planning, technical refinement, demonstrations, release planning, and production support.