Lead Business Analyst

We are looking for a high-impact Lead Business Analyst to drive data engineering and analytics initiatives across enterprise-scale data platforms at IDFC First Bank. This role sits at the intersection of business, product, analytics, and engineering, ideal for someone who can translate complex business problems into scalable data solutions while driving Agile execution across squads.

The ideal candidate will have strong experience in data platforms, business analysis, stakeholder management, Agile delivery, and data-driven product thinking. You will work closely with product owners, data engineers, analytics teams, and business stakeholders to build high-quality data pipelines, reporting systems, and insight-driven solutions. In addition to core BA responsibilities, this role will also act as Scrum Master for the squad and mentor junior business analysts.

The candidate will have responsibilities across the following functions:

Agile Delivery and Squad Execution:

• Own and manage the delivery backlog in collaboration with Product Owners and Data Engineering teams.
• Drive agile ceremonies, including sprint planning, daily stand-ups, retrospectives, and backlog grooming.
• Act as Scrum Master for the squad and ensure smooth sprint execution.
• Track squad velocity, delivery timelines, risks, and dependencies proactively.
• Ensure high-quality and timely execution of data engineering initiatives.

Business and Data Requirement Gathering:

• Translate business requirements into detailed functional and data specifications.
• Define: Source systems and data attributes, business rules and transformations, KPIs, metrics, and reporting logic, dashboards and analytical outputs.
• Create and maintain: BRDs / FRDs, data mappings, workflow diagrams, data flow diagrams, process documentation, and requirement traceability matrices.

Stakeholder and Cross-functional Coordination:

• Collaborate with business, product, analytics, and engineering stakeholders across squads.
• Manage dependencies, issue resolution, and delivery coordination.
• Support governance forums, reviews, and leadership reporting.
• Partner with Product Owners to track customer, business, and engagement funnels through data insights.

Data Validation and Solution Enablement:

• Support data validation, reconciliation, testing, and UAT activities.
• Conduct feature walkthroughs and data solution showcases for stakeholders.
• Ensure delivered solutions align with business expectations and analytical objectives.
• Promote reusable data assets, definitions, and best practices across teams.

Leadership and Process Excellence:

• Mentor junior and mid-level business analysts.
• Drive documentation standards, knowledge management, and process improvements.
• Champion Agile, data-driven, and scalable ways of working.
• Introduce best practices in analytics delivery, requirement management, and stakeholder collaboration.

Requirements:

• Strong experience in business analysis within data engineering/analytics/data platform environments.
• Solid understanding of data warehousing, ETL / ELT pipelines, data transformations, reporting and dashboards, KPIs and business metrics.
• Experience working in Agile / Scrum delivery models.
• Strong stakeholder management and cross-functional coordination skills.
• Ability to understand both business workflows and technical data architectures.
• Hands-on experience creating BRDs, FRDs, data mappings, workflows, and process documentation.
• Excellent communication, prioritisation, and problem-solving abilities.

Good to Have:

• BFSI/banking/fintech domain experience.
• Exposure to cloud data platforms and modern data stacks.
• Experience working with data engineers, BI teams, and analytics squads.
• Familiarity with Jira, Confluence, SQL, Power BI/Tableau, or data governance frameworks.

Secondary Requirements:

• Should have been part of multiple data analysis projects, ideally with a significant focus on text analytics.
• Experience in building, validating, and deploying predictive models based on text data.
• Experience in handling large text datasets, cleaning, and processing text data for machine learning tasks.