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.
Key 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.
Qualifications- 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.
Required Skills :
Basic Qualification :
Additional Skills :
Background Check : No
Drug Screen : No
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 ...
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.
Key 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.
Qualifications- 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.
Required Skills :
Basic Qualification :
Additional Skills :
Background Check : No
Drug Screen : No
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