Sr. Databricks Data Engineer
McLean, VA, US
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll bring
All qualificationsCore experience
- Experience: Minimum of 7 years of professional data engineering experience, including significant hands-on experience with Databricks/Spark and production data pipelines.
- Experience with Unity Catalog, metadata/configuration-driven ingestion, Auto Loader/Lakeflow, Databricks Jobs/Workflows, lineage/cataloging tools, and scalable multi-source ingestion frameworks.
Qualification wording
Experience: Minimum of 7 years of professional data engineering experience, including significant hands-on experience with Databricks/Spark and production data pipelines.
Experience with Unity Catalog, metadata/configuration-driven ingestion, Auto Loader/Lakeflow, Databricks Jobs/Workflows, lineage/cataloging tools, and scalable multi-source ingestion frameworks.
Tools in this posting
- Python
- SQL
- AWS
- Databricks
- Delta
- PySpark
- Spark
- S3
Source — Tool mentions in context
- Collaboration: Partner with the Technical Project Manager, Data Architects, business/data SMEs, BI developers, Cloud/DevSecOps, security, and governance teams to translate requirements into implementable data solutions. - Technical Performance: Develop and optimize Python, PySpark, and SQL workloads using Databricks, Delta Lake, Unity Catalog, Auto Loader and/or Lakeflow capabilities, and Databricks Jobs/Workflows with a focus on reliability, performance, and cost. - Data Quality & Governance: Implement source-to-target reconciliation, data validation, schema evolution, lineage, access controls, documentation, and reusable engineering standards for production data pipelines.
- Experience: Minimum of 7 years of professional data engineering experience, including significant hands-on experience with Databricks/Spark and production data pipelines. - Technical Proficiency: Advanced Python, PySpark, and SQL skills; strong experience with Databricks, Delta Lake, AWS/S3, batch/file ingestion (CSV/JSON), REST APIs, Git/CI/CD, and data pipeline orchestration. - Compliance: Must meet applicable DOT contract security and suitability requirements and demonstrate secure handling of PII and other sensitive data, including access controls and secrets management.
Position Overview The Senior Databricks Data Engineer / Technical Lead will support the U.S. Department of Transportation (DOT) data modernization effort by designing, building, migrating, and operating secure, scalable data pipelines in a Databricks Lakehouse. This is a highly hands-on role focused on legacy and external-source migration, metadata-driven ingestion, Medallion Architecture, data quality and reconciliation, production operations, and transition to the AWS/OneDOT environment. Core Responsibilities
Core Responsibilities - Strategic Execution: Lead the design and implementation of reusable ingestion and transformation patterns for legacy and external data sources into Databricks, including support for migration to the AWS/OneDOT environment. - Operational Oversight: Build and operate Bronze, Silver, and Gold pipelines; manage batch and incremental loads, orchestration, dependencies, retries/recovery, monitoring, alerting, and production support.
- Compliance: Must meet applicable DOT contract security and suitability requirements and demonstrate secure handling of PII and other sensitive data, including access controls and secrets management. - Certifications: Relevant Databricks and/or AWS data engineering certification preferred; equivalent demonstrated hands-on experience will be considered. Preferred Expertise
- Education: Bachelor's degree in computer science, Data Engineering, Information Technology, Engineering, or a related field; equivalent relevant experience may be considered. - Experience: Minimum of 7 years of professional data engineering experience, including significant hands-on experience with Databricks/Spark and production data pipelines. - Technical Proficiency: Advanced Python, PySpark, and SQL skills; strong experience with Databricks, Delta Lake, AWS/S3, batch/file ingestion (CSV/JSON), REST APIs, Git/CI/CD, and data pipeline orchestration.
Preferred Expertise - Demonstrated success modernizing legacy data platforms (Sybase/SAP IQ or similar) into Databricks, including source-to-target reconciliation, cutover, and production stabilization. - Experience with Unity Catalog, metadata/configuration-driven ingestion, Auto Loader/Lakeflow, Databricks Jobs/Workflows, lineage/cataloging tools, and scalable multi-source ingestion frameworks.
- Demonstrated success modernizing legacy data platforms (Sybase/SAP IQ or similar) into Databricks, including source-to-target reconciliation, cutover, and production stabilization. - Experience with Unity Catalog, metadata/configuration-driven ingestion, Auto Loader/Lakeflow, Databricks Jobs/Workflows, lineage/cataloging tools, and scalable multi-source ingestion frameworks. - Federal/DOT delivery experience; familiarity with Agile/Kanban, production O&M, cloud cost optimization, and data governance. Streaming and AI/ML data pipeline exposure is a plus.
Job description
Halvik Corp delivers a wide range of services to 13 executive agencies and 15 independent agencies. Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning, Cyber Security and Cutting-Edge Technology across the US Government. Be a part of something special!
Position Overview
The Senior Databricks Data Engineer / Technical Lead will support the U.S. Department of Transportation (DOT) data modernization effort by designing, building, migrating, and operating secure, scalable data pipelines in a Databricks Lakehouse. This is a highly hands-on role focused on legacy and external-source migration, metadata-driven ingestion, Medallion Architecture, data quality and reconciliation, production operations, and transition to the AWS/OneDOT environment.
Core Responsibilities
- Strategic Execution: Lead the design and implementation of reusable ingestion and transformation patterns for legacy and external data sources into Databricks, including support for migration to the AWS/OneDOT environment.
- Operational Oversight: Build and operate Bronze, Silver, and Gold pipelines; manage batch and incremental loads, orchestration, dependencies, retries/recovery, monitoring, alerting, and production support.
- Collaboration: Partner with the Technical Project Manager, Data Architects, business/data SMEs, BI developers, Cloud/DevSecOps, security, and governance teams to translate requirements into implementable data solutions.
- Technical Performance: Develop and optimize Python, PySpark, and SQL workloads using Databricks, Delta Lake, Unity Catalog, Auto Loader and/or Lakeflow capabilities, and Databricks Jobs/Workflows with a focus on reliability, performance, and cost.
- Data Quality & Governance: Implement source-to-target reconciliation, data validation, schema evolution, lineage, access controls, documentation, and reusable engineering standards for production data pipelines.
Minimum Requirements
- Education: Bachelor's degree in computer science, Data Engineering, Information Technology, Engineering, or a related field; equivalent relevant experience may be considered.
- Experience: Minimum of 7 years of professional data engineering experience, including significant hands-on experience with Databricks/Spark and production data pipelines.
- Technical Proficiency: Advanced Python, PySpark, and SQL skills; strong experience with Databricks, Delta Lake, AWS/S3, batch/file ingestion (CSV/JSON), REST APIs, Git/CI/CD, and data pipeline orchestration.
- Compliance: Must meet applicable DOT contract security and suitability requirements and demonstrate secure handling of PII and other sensitive data, including access controls and secrets management.
- Certifications: Relevant Databricks and/or AWS data engineering certification preferred; equivalent demonstrated hands-on experience will be considered.
Preferred Expertise
- Demonstrated success modernizing legacy data platforms (Sybase/SAP IQ or similar) into Databricks, including source-to-target reconciliation, cutover, and production stabilization.
- Experience with Unity Catalog, metadata/configuration-driven ingestion, Auto Loader/Lakeflow, Databricks Jobs/Workflows, lineage/cataloging tools, and scalable multi-source ingestion frameworks.
- Federal/DOT delivery experience; familiarity with Agile/Kanban, production O&M, cloud cost optimization, and data governance. Streaming and AI/ML data pipeline exposure is a plus.
Halvik offers a competitive full benefits package including:
Company-supported medical, dental, vision, life, STD, and LTD insurance
Benefits include 11 federal holidays and PTO
Eligible employees may receive performance-based incentives in recognition of individual and/or team achievements.
401(k) with company matching
Flexible Spending Accounts for commuter, medical, and dependent care expenses
Tuition Assistance
Charitable Contribution matching
Halvik Corp is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.
Halvik's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on halvik.isolvedhire.com. The employer’s form will show what is required.
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Source & posting history
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- Pay
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- Location & working pattern
McLean, VA, US
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- Status in our records
- Active
- First seen by us
- Sep 21, 2026
- Recorded sightings
- 11
- Last seen by us
- Oct 7, 2026
- Employer says posted
- Sep 15, 2026
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