Lead Data Engineer

Job Title:

About Us

Lead Data Engineer

Key Responsibilities

• Provide strong technical expertise and thought leadership to advise clients on their current and future data landscape.
  
• Design, build, and optimize scalable data pipelines using Spark, ensuring high performance and reliability.
  
• Collaborate with client Machine Learning engineers to define and enhance

  MLOps

  and

  LLMOps

  processes.
• Support ML teams in productionizing GenAI workflows; possess working knowledge of GenAI workflows (hands-on experience preferred).
  
• Work extensively with

  Databricks

  for data engineering and pipeline management strong experience is mandatory.
• Partner with the client Product Owner to identify resource requirements, manage resource allocation across streams, and support planning of milestones and release cycles.
  
• Lead and mentor a team of engineers, ensuring effective delivery, performance management, and knowledge sharing.
  

Required Skills & Qualifications

• 915 years of relevant experience in Data Engineering.
  
• Expertise in Spark, Databricks, and large-scale distributed data processing.
  
• Strong understanding of cloud-based data platforms and modern data architecture.
  
• Hands-on experience working on MLOps / LLMOps workflows with ML lifecycle familiarity.
  
• Good knowledge of GenAI tools, ecosystem and implementation patterns.
  
• Strong communication, stakeholder management, and team leadership skills.
  
• Ability to work in a client-facing environment with collaborative execution.
  

Preferred Qualifications

• Experience with Azure/AWS/GCP data engineering stacks.
  
• Exposure to CI/CD, DevOps practices within data engineering environments.
  
• Industry certifications in Databricks or cloud technologies.