Data Ops Developer

CMT Services Inc • Washington, DC

1d • Remote

About The Position

The Data Ops Developer will support the USDA’s Enterprise Human Capital Modernization & Transformation initiative. In this role, the Data Ops Developer builds and maintains automated data pipelines, ETL/ELT workflows, and CI/CD automation. Ensures data reliability, monitors performance, and supports DevSecOps practices.

Requirements

• 3 to 5 years of progressive professional experience in data engineering, ETL/ELT development, data integration, data migration, or a related field.
• Experience building and maintaining automated data pipelines and ETL/ELT workflows supporting HCM data migration, integration, and the USDA Databricks Lakehouse.
• Experience implementing data transformation, validation, reconciliation, load sequencing, data quality controls, and exception handling supporting initial and iterative HCM data conversion. The PWS requires profiling, source-to-target mapping, transformation, validation, reconciliation, loading, and migration-readiness controls.
• Experience supporting ETL/ELT pipelines, middleware, integration platforms, and cloud-native integration services, including troubleshooting data transformation and performance issues across environments.
• Experience developing or supporting automated testing and reconciliation processes used to verify data lineage, accuracy, and completeness during mock migrations and UAT.
• Experience supporting CI/CD automation, data reliability, performance monitoring, and DevSecOps practices for enterprise data solutions.

Responsibilities

• Core Deliverables: Data pipelines, ETL/ELT, migration execution, testing, automation, Lakehouse implementation.
• Data Migration Planning & Coordination: Migration strategy, plans, timelines, crosswalks, mapping rules, trial migrations, reconciliation
• Data Quality & Cleansing: Data quality assessments, dashboards, cleanup campaigns, standards compliance
• Systems Integration Engineering: APIs, integrations, interface design, ICDs, ETL/ELT pipelines, interface remediation, integration testing
• Testing & Validation: Test cases, reconciliation scripts, UAT coordination, data verification
• Databricks Lakehouse Support: Lakehouse architecture, security design, common data model, migration framework, reporting and analytics

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level