01Overview
Role & responsibilities
Product Owner with Databricks, Analytics & AI proficiency 9+ Years (Candidates must have strong hands-on experience in Product Ownership/Product Management with a proven track record of delivering Analytics, AI/GenAI, and Databricks-based products. Strong expertise in Agile and SAFe methodologies with experience managing product roadmaps, sprint planning, backlog prioritization, user story creation, acceptance criteria, and stakeholder management is mandatory. Candidates should possess strong knowledge of Databricks including Delta Lake, Unity Catalog, Databricks SQL, and Lakehouse architecture, along with experience working on Azure Data Platform including Azure Data Factory (ADF), Azure Synapse Analytics, and Azure Data Lake Storage (ADLS).
Good understanding of Data Engineering concepts such as ETL/ELT, Data Warehousing, Data Pipelines, and Data Integration is essential. Candidates should have strong SQL skills and a working knowledge of Python/PySpark to effectively collaborate with engineering teams.
Experience with JIRA, Confluence, Agile ceremonies, release planning, and cross-functional product delivery is required. Exposure to Financial Services, Banking, Risk, or Assurance domains is preferred. Please do not share profiles with only Project Management, Business Analysis, or Delivery Management experience without Product Ownership responsibilities.
Candidates must have strong Databricks, Analytics, AI/GenAI, Azure Data Platform, and Product Ownership expertise with hands-on experience in delivering enterprise-scale data and AI products.
Preferred candidate profile .
