Lead Data Engineer

Lead Data Engineer Hybrid Onsite in Washington DC Rate: 59/hr on C2C 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: 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.