
Mng. Consultant - Databricks Data Engineering Lead with Security Clearance
Why this role stands out
Advance your career by leading high-impact data modernization projects for the federal government, where you will leverage cutting-edge Databricks technology in a flexible hybrid work environment. This role is perfect for a skilled engineer who thrives on building scalable ETL solutions and collaborating with expert teams to solve complex data challenges. Apply today to secure your place in this mission-critical initiative and elevate your technical expertise.
Quick overview
Job description
Company: Supporting the Federal Gov Positions: Mid, senior and lead Databricks openings REMOTE MUST BE US CITIZEN. MUST BE PROCESSED FOR E PUBLIC TRUST CLEARANCE Benefits: Healthcare and 401k NOTE; FOR A QUICKER RESPONSE, PLEASE APPLY DIRECT TO and put "Databricks" on the subject line. Thank you! Job Description Summary Builds and tests Databricks pipelines, transformations, migration workflows, quality controls, APIs, curated datasets, reconciliation routines, and reusable data products supporting a large federal human-capital data modernization program.
What You Will Do • Build and maintain Databricks ingestion, transformation, orchestration, migration, and data-processing pipelines. • Develop scalable ETL/ELT solutions using Databricks, Apache Spark, PySpark, Python, SQL, and Delta Lake. • Implement source-to-target mappings, transformation rules, business logic, data contracts, metadata, lineage, and data-quality requirements. • Develop migrated data feeds, APIs, curated datasets, reporting layers, and reusable data products. • Create reconciliation routines and support source-to-target validation, exception analysis, and defect resolution. • Build unit, integration, regression, performance, and data-quality tests and document technical results. • Support Git-based development, CI/CD, release management, deployment, monitoring, troubleshooting, and stabilization. • Analyze and resolve job failures, cluster-performance issues, pipeline bottlenecks, schema changes, and data-quality problems. • Collaborate with data architects, engineering leads, integration engineers, profiling analysts, testers, security specialists, governance leads, and source-system teams. • Document reusable code, technical patterns, runbooks, troubleshooting procedures, and lessons learned for later modernization waves. • Participate in Agile ceremonies, backlog refinement, sprint planning, demonstrations, and technical reviews.
What You Will Need • Bachelor's degree in computer science, data engineering, information systems, engineering, analytics, or a related field. • Minimum 4 years of experience in data engineering, software development, ETL/ELT, cloud analytics, or a related technical discipline. • Hands-on experience with Databricks, Apache Spark, PySpark, Python, SQL, Delta Lake, and workflow orchestration. • Experience building, testing, and maintaining batch data pipelines, transformations, and curated data layers. • Experience with enterprise data migration, source-to-target mapping, reconciliation, validation, and data-quality controls. • Familiarity with Git, CI/CD, automated testing, deployment, monitoring, logging, and troubleshooting. • Strong analytical, problem-solving, documentation, collaboration, and communication skills. • Ability to obtain and maintain a Federal Public Trust.
Medical, dental, and vision insurance are available to qualified candidates who meet eligibility requirements.
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