Lead Data Engineer (Databricks & AI)

Randstad 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: Bachelor's 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.

Required Skills :

Basic Qualification :

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Background Check : No

Drug Screen : No