Business Analyst

Role Overview :

We are looking for a highly skilled Business Analyst with strong Data & Analytics experience to work with MDH (Mobility Data Hub) & its related Hubs & capabilities.

The role involves driving data requirement gathering, translating business needs into technical specifications (such as Source to Target mapping ; process flows etc.), and contributing to data lineage, data quality and governance initiatives.

The ideal candidate will have experience in Azure data platforms, interest in Databricks Unity Catalog and data quality tools and strong collaboration skills to work with multiple cross functional stakeholders.

Key Responsibilities :

1. Requirements Gathering & Analysis :

- Engage with business stakeholders to understand data needs, business rules, and analytical requirements.

- Conduct detailed requirement elicitation, including interviews, workshops, process walk throughs, and document analysis.

- Translate business requirements into clear, structured BRDs, FSDs, and User Stories with acceptance criteria.

- Validate feasibility of requirements by assessing data sources, data flows, platform capabilities, and downstream dependencies.

- Ensure end to end traceability from requirements data design development testing deployment

2. Data Analysis & Modelling :

- Analyze existing and new Retail datasets, their relationships, quality gaps, and lineage.

- Drive Source-to-Target Mapping (S2T) and support data modeling discussions with architects and engineers.

- Collaborate with the MDH team to evaluate data ingestion pipelines, transformations, and data assurance processes.

- Support profiling of large datasets using SQL, Databricks notebooks, and other enterprise tools.

3. Platform & Technology Collaboration :

- Work directly with engineering teams to understand Azure ecosystem components (Data Factory, Data Lake, Databricks, SQL, AI Foundary).

- Actively explore and co drive adoption of Databricks Unity Catalog, data quality frameworks, and governance tools as part of the AI Data Foundation layer.

- Assess limitations and opportunities of Cloud-native data engineering patterns

4. Stakeholder & Delivery Management :

- Coordinate closely with Product Owners, Architects, Data Engineers, Testers, and vendor teams.

- Facilitate requirement clarification sessions, design reviews, and sprint ceremonies.

- Communicate risks, issues, and data gaps proactively.

- Support test teams by reviewing test scenarios and validating alignment with business expectations

5. Documentation & Governance :

- Maintain high-quality documentation across requirement specifications, process flows, S2T maps, and decision logs.

- Ensure compliance with data governance, quality, and security standards.

- Contribute to business cases, value assessment, and benefit realization discussions.

Required Skills & Experience :

Technical & Data Skills :

- Solid understanding of Azure Data Platform components (Data Factory, ADLS, Azure SQL, Databricks).

- Strong SQL skills (querying, profiling, validation).

- Hands on experience with data requirement analysis, S2T mapping, and data modeling concepts.

- Familiarity or strong interest in Databricks Unity Catalog, Data Quality frameworks, and ML/AI-enabling data architectures.

- Understanding of data pipelines, ETL/ELT patterns, and cloud-based data integration.

Business & Analytical Skills :

- 710 years of experience in Business Analysis in IT/Data/Digital projects.

- Strong ability to interpret business needs and convert them into functional and technical requirements.

- Experience working in Agile Scrum environments.

- Strong ability to facilitate discussions, simplify complex concepts, and align diverse stakeholder groups.

Soft Skills :

- Excellent communication, documentation, and presentation skills.

- Highly self driven, structured, and proactive in problem-solving.

- Ability to collaborate across time zones and work with global teams.

- Strong stakeholder management and negotiation skills.

Preferred Skills :

- Experience in Retail/Fuels/Mobility domain.

- Exposure to Data & Analytics tools on Azure or AWS

- Understanding of AI/ML project lifecycle and associated data needs.

- Certifications such as CBAP, PMI PBA, Agile, Azure Data Fundamentals.

Education :

- Bachelors Degree in Computer Science, Information Systems, Engineering, or relevant technical discipline.