Databricks Tech Lead
Indexed description
Job Title: Databricks Technical Lead
Location: Washington, DC Metro Area
Work Arrangement: Hybrid — approximately 4 days/week onsite (core hours 10 AM–2 PM), with some flexibility depending on client needs. Occasional travel to the client's Rosslyn location possible (e.g., PI Planning).
Position Overview
We are seeking a Databricks Technical Lead to lead a team of four data engineers supporting a high-profile federal client environment. This is a hands-on technical leadership role — you'll provide direction to experienced engineers, serve as the primary technical point of contact for the client, and jump into the details yourself when pipeline failures or complex issues arise. This is a great fit for a senior consultant / second- or third-year consulting-level professional ready for more technical leadership and client-facing responsibility while staying close to the work.
Key Responsibilities
- Lead and provide technical direction to a team of four data engineers, including senior engineers who require limited day-to-day oversight.
- Serve as the primary technical point of contact for the client, translating business and technical requirements into effective data engineering solutions.
- Provide architecture, design, and implementation guidance across data pipelines and Databricks-based solutions.
- Establish best practices with the team, troubleshoot technical challenges, and review code and technical solutions.
- Get into the trenches when pipeline failures or production issues arise.
- Help establish standards around development, testing, deployment, monitoring, and operational support.
- Communicate technical status, risks, and recommendations to project and client leadership.
- Mentor engineers and foster a collaborative, technically strong team environment.
Required Qualifications
- Strong hands-on experience with Databricks, or a comparable modern data platform (e.g., 10+ years on Snowflake) with strong transferable data engineering skills.
- Strong proficiency with PySpark and Python.
- Multiple years of data engineering experience, with demonstrated ability to design and troubleshoot data pipelines.
- Experience providing technical leadership or guidance to other engineers, with enough credibility to direct experienced engineers without excessive hand-holding.
- Strong client-facing communication skills, able to explain technical concepts to technical and non-technical stakeholders alike.
- Experience working in a consulting or client-services environment.
Nice-to-Have Qualifications
- JavaScript/front-end development or cloud engineering experience beyond core data engineering.
- Exposure to DevOps, CI/CD, or infrastructure automation (Azure DevOps a plus).
- Experience with AWS, Azure, or GCP.
- Agile experience, including PI Planning.
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