Lead Data Engineer (Databricks & AI)

Client is seeking a high-impact Lead Data Engineer to drive the next generation of data and AI solutions for a premier client in the transportation sector located in Washington D.C. In this hybrid hands-on leadership role you will spearhead the design and deployment of enterprise-scale Databricks pipelines while mentoring a team of talented engineers. You will serve as the technical bridge between executive strategy and production-grade execution ensuring that AI capabilities are not only innovative but also secure scalable and aligned with modern governance standards. If you are a seasoned engineer who thrives on solving complex architectural challenges while remaining in the code this is your opportunity to power the digital transformation of a national icon.

• Technical Leadership: Lead the end-to-end design development and deployment of enterprise-scale data and AI solutions within a Databricks environment.
• Mentorship: Act as a technical catalyst for the team providing hands-on guidance in Python Scala or Java and fostering a culture of engineering excellence through code reviews and skills development.
• Pipeline & Model Delivery: Oversee the construction of complex data pipelines model deployment (MLOps) and integration patterns from concept through to production.
• Strategic Collaboration: Partner with architects product owners and governance leads to ensure all data systems align with the broader enterprise strategy and security policies.
• Optimization: Drive continuous improvements in platform efficiency observability and data quality to ensure high-performance delivery across multiple product teams.

• Experience: 6 8 years of experience in data engineering or AI systems development showing a clear trajectory of increasing technical leadership.
• Technical Mastery: Advanced proficiency in SQL Python (or Scala/Java) and the Databricks ecosystem.
• Architectural Knowledge: Proven success in leading the delivery of complex data integrations cloud platforms and AI-driven initiatives.
• Process Expertise: Strong background in Agile methodologies MLOps and enterprise data governance standards.
• Education: Bachelors degree in Computer Science Information Systems or a related technical field (equivalent professional experience considered).
• Soft Skills: Exceptional problem-solving abilities and the communication skills necessary to navigate stakeholders and technical challenges simultaneously.

Job Responsibilities

Technical Leadership: Lead the end-to-end design development and deployment of enterprise-scale data and AI solutions within a Databricks environment.

Mentorship: Act as a technical catalyst for the team providing hands-on guidance in Python Scala or Java and fostering a culture of engineering excellence through code reviews and skills development.

Pipeline & Model Delivery: Oversee the construction of complex data pipelines model deployment (MLOps) and integration patterns from concept through to production.

Strategic Collaboration: Partner with architects product owners and governance leads to ensure all data systems align with the broader enterprise strategy and security policies.

Optimization: Drive continuous improvements in platform efficiency observability and data quality to ensure high-performance delivery across multiple product teams.