Data Engineer - Databricks
- Hiring from
- United States
- Work type
- Remote
- Posted
- Sep 29, 2026
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.
- 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?
- 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.
- 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).
- 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