Business Analyst - (Data Lakehouse | Banking )

You will own requirements discovery and translation into high‑quality user stories for the build and commissioning of an on‑prem Data Lakehouse on Cloudera CDP 7.3.1 using Medallion architecture and Lambda architecture (batch + streaming + serving).
Operating in retail and corporate banking domains, you will ensure alignment to SAMA regulatory/compliance expectations, facilitate KT sessions in discovery, schedule and conduct stakeholder interviews, maintain clear, testable acceptance criteria, and support the Test Lead during validation/UAT.
Strong listening, liaison, and stakeholder management skills are essential.

• Well‑formed backlog of epics, features, and user stories with clear acceptance criteria, traceable to business objectives and regulatory needs.
• Requirements sign‑off achieved per sprint/release with stakeholder consensus and minimal rework.
• Testable outcomes: stories mapped to test cases; UAT support provided; defects triaged quickly to closure.
• Compliance & data governance alignment: requirements reflect SAMA obligations, data privacy/PII handling, and metadata capture (Axon).
• Effective liaison across business, data modelling, ETL, and architecture teams—ensuring timely delivery and clarity.

• 5+ years in Business Analysis, with 3+ years in banking/financial services.
• Strong understanding of retail & corporate banking processes and products (loans, cards, deposits, wealth management).
• Familiarity with SAMA regulatory/compliance expectations and audit readiness in KSA contexts.
• SQL proficiency for data validation and requirement verification (joins, aggregations, basic analytics/window functions preferred).
• Hands‑on experience with agile SDLC (Scrum/Kanban), Jira/Confluence, and story writing with acceptance criteria.
• Excellent listening, communication, and stakeholder management; proven liaison skills across business and technical teams.
• Strong documentation discipline; ability to create clear BRDs/FRDs, RTMs, and workshop outputs.

• Exposure to CDP 7.3.1, Medallion/Lambda architecture, Informatica ETL, Informatica Axon (metadata/governance), and Denodo (semantic virtualization).
• Awareness of table formats and serving stores (Iceberg, Hudi, Kudu, HBase + Phoenix) and what they imply for requirements (e.g., latency, upsert, time‑travel).
• Understanding of data quality (DQ) and lineage needs; experience defining data contracts.