Skills/Experience:
- Experience: 8+ years in Data Engineering/Architecture, with at least 3+ years of hands-on leadership within the Databricks ecosystem.
- Core Tech: Expert-level knowledge of the Spark framework (PySpark/Scala), Delta Lake, and Databricks SQL.
- AI/ML Expertise: Proven experience building and deploying AI solutions. Deep understanding of the Agentic AI landscape—moving beyond simple chatbots to autonomous, goal-oriented agents.
- FinOps Mastery: Specific experience in Databricks cost management, instance selection, and performance tuning (Z-Ordering, Liquid Clustering).
- Data Management: Strong background in data modelling and the creation of reusable ETL/ELT templates and frameworks.
- Insurance Domain: Prior experience in the Insurance or FinServ sector is highly preferred; you must understand the nuances of policy-centric data.
- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
- Preferred: Databricks Certified Data Engineer Professional or Databricks Certified Machine Learning Professional.

