Business Data Analyst

In this role, you will collaborate closely with one of our esteemed clients—a globally recognized leader in their industry, distinguished by their commitment to excellence, innovation, and delivering exceptional value. As a trusted IT consulting partner, Dautom is supporting their strategic initiatives by connecting them with exceptional talent to drive business growth and transformation.

About the role :

Role Name : Senior Manager – Business Data Analyst

Job Purpose :

We are seeking an experienced Banking Data Analyst with 7–12 years of experience to support Retail Banking data initiatives. The ideal candidate should have strong knowledge of retail wealth investment, loan, CASA products along with hands-on expertise in SQL, Excel, Generative AI, data mapping, data lineage, and data quality reconciliation. The role involves working closely with business stakeholders to gather and analyze requirements, prepare BRDs and Functional Specification Documents (FSDs), and support data analysis across Data Lake, Data Mart, and Hive-based environments while ensuring data accuracy and consistency.

Key Result Areas :

• Collaborate with business stakeholders to gather, analyze, and document business requirements across retail banking (wealth and lending).
• Prepare and maintain Business Requirement Documents (BRD) and Functional Specification Documents (FSD).
• Translate business requirements into detailed data mapping and technical specifications.
• Drive data analysis and contribute to the design and implementation of OneData platform solutions.
• Work closely with business, technology, and data engineering teams to ensure accurate implementation of requirements.
• Support data modelling, data lineage, and reconciliation activities.
• Work with enterprise data environments including Data Marts, Data Lakes, and Hive-based platforms.
• Analyze and validate retail lending data across various banking platforms.
• Ensure data quality and consistency across wealth and loan data domains.
• Collaborate with cross-functional teams to enable end-to-end portfolio and onboarding journey insights.
• Strong communication skills (verbal/written) to deliver technical insights and interpret data reports to the clients. Also helps in understanding and serving the client's requirements.
• Leverage Generative AI tools to improve data analysis, productivity, and reporting processes.

Knowledge, Skills, and Experience

Core Skills:

Min experience 7-12 years as a Data Analyst within the Banking or Financial Services industry.

Functional Expertise

• The candidate must have strong knowledge in Retail Banking, with focus on:

Loan & Liability Products

• Working knowledge of retail products including:
• Retail wealth investment products including equities, mutual funds, Bonds, ETF etc
• Loans
• CASA (Current Account & Savings Account)
• OD (Overdraft) products
• Other Retail Lending Products

Customer Journey Understanding

• Customer onboarding journeys
• Portfolio creation and lifecycle management

Data & Analytics Skills

• Strong SQL skills, including Complex Queries, Data Validation, Data Analysis and Troubleshooting, Query Optimization
• Hands-on experience working with data Lakes, Data Marts, Hive or similar big data environment, enterprise data platforms.
• Advanced Excel skills for data analysis and reconciliation.
• Experience working with Generative AI tools and use cases in data analytics.
• Strong understanding of Data Mapping and source-to-target transformation logic.
• Experience in Data Quality Management and Data Reconciliation activities.
• Understanding of data warehousing concepts and data modelling principles.

Documentation & Analysis

Experience preparing:

• Business Requirement Documents (BRD)
• Functional Specification Documents (FSD)
• Data Mapping Documents
• Functional and Technical Documentation

Additional Skills Desired:

• Good Communication Skills
• Strong Analytical Thinking
• Confident in decision making and the ability to explain processes or choices as needed.
• Ability to manage multiple priorities and work collaboratively across teams.

Education

• Bachelor's degree in Computer Science, Engineering, Finance, or related discipline.

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