Lead Business Analyst (Data Engineering)

This role is for one of the Weekday's clients

Salary range: Rs 2000000 - Rs 6000000 (ie INR 20-60 LPA)

Min Experience: 7 years

Location: Mumbai

JobType: full-time

We are looking for a highly driven Lead Business Analyst to lead enterprise-scale data engineering and analytics initiatives in a fast-paced, technology-driven environment. This role is ideal for someone who can bridge the gap between business, analytics, product, and engineering teams while driving structured Agile execution across data-focused squads.

As a Lead Business Analyst, you will play a critical role in translating complex business problems into scalable data solutions. You will work closely with Product Owners, Data Engineers, Analytics teams, and business stakeholders to define data requirements, streamline workflows, and deliver impactful analytics-driven solutions. In addition to core business analysis responsibilities, this role also requires Scrum Master capabilities and the ability to mentor junior analysts while driving delivery excellence.

The ideal candidate should possess strong expertise in business analysis within data engineering or analytics ecosystems, with a deep understanding of data flows, KPIs, reporting systems, ETL processes, and Agile delivery practices.

• Collaborate with business stakeholders, product teams, analytics teams, and data engineers to gather and analyze business requirements.
• Translate business requirements into detailed functional specifications, data mappings, workflows, and analytical requirements.
• Define business rules, KPIs, reporting logic, source systems, and transformation requirements.
• Create and maintain documentation including BRDs, FRDs, process flows, data flow diagrams, requirement traceability matrices, and workflow documentation.
• Own and manage Agile delivery backlogs in collaboration with Product Owners and engineering teams.
• Act as Scrum Master for the squad by facilitating sprint planning, stand-ups, retrospectives, backlog grooming, and delivery tracking.
• Monitor squad velocity, dependencies, risks, and delivery timelines proactively.
• Support data validation, reconciliation, testing, UAT activities, and stakeholder walkthroughs.
• Ensure delivered data solutions align with business goals, analytical objectives, and reporting requirements.
• Coordinate cross-functional dependencies and manage issue resolution across teams.
• Drive governance discussions, leadership reporting, and delivery updates.
• Promote reusable data assets, standard definitions, and scalable best practices across projects.
• Mentor junior Business Analysts and contribute to process improvement initiatives.
• Champion Agile methodologies, structured documentation practices, and data-driven decision-making frameworks.

• Strong experience in Business Analysis within Data Engineering, Analytics, Data Warehousing, or Data Platform environments.
• Deep understanding of ETL/ELT pipelines, data transformations, reporting systems, dashboards, and business metrics.
• Hands-on experience creating BRDs, FRDs, workflows, data mappings, and process documentation.
• Strong knowledge of Agile and Scrum delivery methodologies with experience driving sprint execution.
• Excellent stakeholder management and cross-functional collaboration skills.
• Ability to understand both technical data architectures and business workflows effectively.
• Strong analytical thinking, prioritization, and problem-solving capabilities.
• Experience working with Data Engineers, BI teams, Analytics squads, and Product Owners.
• Familiarity with tools such as Jira, Confluence, SQL, Power BI, Tableau, or similar analytics platforms is preferred.
• Exposure to cloud data platforms, modern data stacks, or data governance frameworks is an advantage.
• Banking, BFSI, or Fintech domain experience is highly preferred.
• Experience working on data-heavy or text analytics projects is a strong plus.
• Ability to mentor teams, drive execution discipline, and operate effectively in high-ownership Agile environments.