Data Engineer - Databricks
Description
At MetaPhase, we believe Quirky is Cool and being authentic is the only way to be! We take the work we do very seriously and do a lot of important mission-focused work for our clients. We are individuals with different passions and strengths who take as much joy in the work we do as from those we work with. Today, we have a team that is invested in creating new solutions that lean forward, challenge the status quo, but also reflect our intimate knowledge of our customers’ business. Over the years we have fostered a culture in which we are united by shared values—passion, solidarity, generosity, curiosity, and boldness—and these come alive in the work we do and how we do it.
Together, we know our people are our difference—for our clients and our colleagues.
Are you ready to:
- Work alongside a dedicated and diverse set of people to offer honest advice and practical guidance to our clients?
- Learn and grow by taking advantage of every opportunity available to you?
- Join a company which prides itself on its shared values and inclusive culture?
- Be the difference and make it happen?
Role Summary
The Data Engineer – Databricks will support the design, development, testing, deployment, operation, and continuous improvement of data pipelines and data products within a Databricks environment. Working under the direction of the Principal Databricks Architect / Engineer and delivery leadership, this role will convert approved data requirements into reliable, well-documented, and supportable code. The engineer will contribute to data governance, platform operations, troubleshooting, and sustainment while building practical expertise in Databricks engineering patterns and enterprise data delivery.
What You Will Be Doing
- Develop, test, deploy, and maintain batch and streaming data pipelines using Databricks, Python, SQL, Apache Spark, and Delta Lake.
- Build and enhance ingestion, transformation, validation, and publishing processes that move data from source systems into governed data products and analytics-ready datasets.
- Implement approved data models, data-quality rules, metadata, and documentation in accordance with established architecture and governance standards.
- Configure and maintain Databricks notebooks, workflows, jobs, compute resources, and related deployment artifacts.
- Participate in code reviews, peer testing, release preparation, defect remediation, and CI/CD activities.
- Monitor pipeline performance, job execution, data-quality results, and platform alerts; troubleshoot issues and support resolution of production incidents.
- Collaborate with architects, analysts, data owners, and other engineers to clarify requirements, identify dependencies, and deliver iterative improvements.
- Maintain technical documentation for pipelines, data sources, transformations, interfaces, test results, and operating procedures.
What We Need From You (Required)
- Bachelor’s degree in a technical discipline and three or more years of relevant experience in data engineering, software engineering, analytics engineering, or a related field.
- Demonstrated proficiency in Python and SQL, with experience developing, debugging, and maintaining ETL/ELT processes and data-processing code.
- One or more years of hands-on experience with Databricks, Apache Spark, or a comparable cloud data-engineering platform.
- Experience working with structured and/or unstructured data sources, data validation, source-to-target mapping, and production-support activities.
- Databricks Certified Data Engineer Associate certification preferred; candidates without the certification must be willing to obtain it within three months of start date.
- Ability to obtain a U.S. Public Trust suitability determination.
- U.S. Citizenship Required(Clearance / Citizenship Requirements).
Bonus Points (Desired)
- Experience with Databricks capabilities such as Delta Lake, Auto Loader, Databricks SQL, Lakeflow Jobs, Unity Catalog, or streaming data pipelines.
- Familiarity with Git-based version control, code reviews, automated testing, CI/CD, and Agile delivery practices.
- Experience supporting data governance activities, including metadata documentation, data-quality checks, lineage, and access-control implementation.
- Experience with AWS, Azure, or Google Cloud data services and cloud-based integrations.
- Experience supporting regulated, public-sector, or security-sensitive data environments.
- Additional Databricks certifications (e.g., Databricks Machine Learning Engineer Associate or Professional, Databricks Generative AI Engineer Associate)
Work Location
Remote (travel 5%)Education BA/BS in a Technical Discipline Clearance Requirements Must be able to obtain a U.S. Public Trust suitability determination. U.S. Citizenship Required.
Benefits & Perks At MetaPhase, we care about your well-being and success. Our benefits include generous PTO, federal holidays, parental leave, comprehensive health coverage (medical, dental, vision, life, and disability), 401(k) with company match, FSA/HSA options, commuter benefits, and much more.
About MetaPhase
MetaPhase is different with a purpose — demonstrating a new approach to the industry that puts employees and culture first. We continue to be recognized by industry as one of the fastest-growing and most impactful consultancies in the nation. MetaPhase is an equal opportunity employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, national origin, disability or veteran status, or any other factors protected