Data Ops Developer

CMT SERVICES, Inc.

. Build and maintain automated data pipelines and ETL/ELT workflows .

Posted 9/17/2026contractWashington • District of Columbia • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining automated data pipelines and ETL/ELT workflows, with a strong focus on data migration and integration within the USDA Databricks Lakehouse environment. Proficient in data quality assessments, CI/CD automation, and supporting DevSecOps practices to ensure data reliability and compliance.

Highest-signal resume keywords

Data EngineeringETL/ELT DevelopmentHCM Data MigrationCI/CD AutomationData Quality Controls

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Automated Data PipelinesData IntegrationData MigrationData TransformationData ValidationData ReconciliationAPI EngineeringIntegration TestingPerformance MonitoringData Lineage

Tools & Technologies

USDA Databricks LakehouseMiddlewareIntegration PlatformsCloud-Native Integration ServicesDevSecOps Practices

Industry Keywords

Data Quality AssessmentMigration StrategiesUAT CoordinationCommon Data ModelsReporting and Analytics

Tech Stack

Tools & technologies

CloudETL

About the role

Key responsibilities & impact

Build and maintain automated data pipelines and ETL/ELT workflows
Support HCM data migration, integration, and the USDA Databricks Lakehouse
Plan and coordinate migration strategies, plans, timelines, crosswalks, mapping rules, trial migrations, and reconciliation
Conduct data quality assessments, create dashboards, run cleanup campaigns, and ensure standards compliance
Engineer APIs, integrations, interface designs, ICDs, ETL/ELT pipelines, interface remediation, and integration testing
Develop test cases and reconciliation scripts, coordinate UAT, and perform data verification
Support Lakehouse architecture, security design, common data models, migration frameworks, reporting, and analytics
Automate CI/CD processes, monitor performance, ensure data reliability, and support DevSecOps practices

Requirements

What you’ll need

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 for HCM data conversion
Experience with 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
Experience troubleshooting data transformation and performance issues across environments
Experience developing or supporting automated testing and reconciliation processes for 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
Bachelor's degree in Computer Science, Information Systems, Information Technology, or Computer Engineering

Benefits

Comp & perks

One 1-year base period plus 1-year option periods
Mostly remote work arrangement
Supportive, collaborative environment
Career advancement opportunities