Lead Data Engineer (Databricks & AI)Location: Washington, DC (Onsite) Key ResponsibilitiesTechnical 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.QualificationsExperience: 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.