Lead Business Analyst

The Lead Business Analyst - Data Management & Analytics plays a critical role in connecting business needs with data and technology delivery. This position leads business analysis efforts for data-driven projects by translating complex business requirements into detailed documentation, including business rules, data requirements, functional specifications, and actionable plans. The role involves close collaboration with business stakeholders, data owners, application teams, data engineers, governance teams, and technical developers to ensure data solutions meet business objectives while maintaining high standards of data quality, governance, traceability, and regulatory compliance.

Key Responsibilities

Business Analysis & Requirements Management
Lead requirement-gathering sessions with stakeholders and subject-matter experts. Facilitate workshops, walkthroughs, validation sessions, and discussions to clarify business needs. Translate these into comprehensive Business Requirement Documents (BRDs), functional requirements, business rules, data requirements, and acceptance criteria. Analyze business processes to identify gaps, dependencies, and opportunities for improvement. Ensure requirements are clearly understood, traceable, and managed throughout the solution delivery lifecycle. Handle requirement changes and assess their impact on business and data.

Data Analysis & Business Rules
Examine source systems, datasets, data availability, and flows to verify support for business requirements. Define and document business rules, calculation logic, validation criteria, thresholds, exceptions, and reporting needs. Collaborate with technical teams to convert business rules into data transformations, analytical logic, and reporting solutions. Validate data outputs against approved requirements and expected outcomes. Conduct root-cause analysis for data discrepancies, quality issues, and reporting gaps.

Data Management & Governance
Assist stakeholders in identifying and defining Critical Data Elements (CDEs). Support data ownership, stewardship, business glossary, metadata, and data-domain activities. Align business requirements with data governance policies and organizational standards. Work with Data Governance and Data Quality teams to identify and resolve data-quality issues. Define data-quality rules and validation requirements based on business expectations. Support regulatory and governance initiatives, including NDMO and PDPL compliance where applicable.

Analytics & Reporting
Lead business analysis for data analytics, dashboards, management reporting, and business intelligence projects. Gather and validate reporting requirements from users. Define KPIs/KRIs, calculation logic, thresholds, exception criteria, reporting frequency, and expected outputs. Review dashboards and reports to ensure alignment with approved business requirements. Support User Acceptance Testing (UAT) by defining test scenarios, validating results, clarifying defects, and obtaining sign-off.

Stakeholder & Delivery Management
Serve as the primary liaison between business stakeholders and technical delivery teams. Coordinate with data owners, application owners, DBAs, data engineers, developers, and other technology teams. Track requirements, dependencies, risks, issues, and delivery actions. Facilitate status meetings, workshops, walkthroughs, and decision-making sessions. Support project planning, documentation, operational readiness, go-live planning, post-production validation, issue resolution, and knowledge transfer.

Solution & Technical Collaboration
Collaborate closely with Data Engineers and Solution Architects to ensure solutions meet business requirements. Understand data integration, ETL/ELT, data warehouse, data lake/lakehouse, metadata, and data-quality concepts to challenge and validate technical solutions. Analyze SQL datasets and technical metadata to verify requirements and investigate data issues. Review data mappings and source-to-target specifications. Participate in solution walkthroughs and provide business analysis input to technical design decisions.

Required Qualifications

- Minimum 5 years of experience in Business Analysis, Data Management, Data Analytics, Business Intelligence, or related fields.
- Proven ability to gather and document business requirements effectively.
- Experience working across both business and technical teams.
- Strong understanding of data analysis, data quality, data integration, and reporting.
- Skilled in defining business rules, data requirements, KPIs/KRIs, and validation criteria.
- Experience supporting UAT, stakeholder validation, and solution acceptance.
- Familiarity with data governance, metadata, data ownership, and data-quality concepts.
- Background in banking, financial services, or other regulated industries preferred.
- Knowledge of regulatory/data-management frameworks such as NDMO and PDPL is advantageous.

Preferred Qualifications and Benefits

- Strong SQL and data analysis skills.
- Understanding of ETL/ELT processes and data integration concepts.
- Familiarity with Data Warehouse, Data Lake, and Lakehouse architectures.
- Experience with BI and visualization tools such as Power BI or Tableau.
- Knowledge of data-quality management and profiling techniques.
- Understanding of metadata and data catalog concepts.
- Experience with data governance platforms like Informatica Axon or EDC is a plus.
- Exposure to data platforms such as Informatica, Cloudera, or Alteryx is advantageous.
- Excellent stakeholder management, communication, analytical, and problem-solving skills.
- Ability to lead workshops, facilitate senior stakeholder discussions, and translate complex technical concepts into clear business language.
- Strong organizational skills with the ability to manage multiple initiatives simultaneously.
- Bachelor’s degree in IT, Computer Science, Engineering, Business, Data Management, or related discipline.
- Professional certifications in Data Management, Business Analysis, or Data Governance are preferred.

This role offers the opportunity to work at the intersection of business and technology, driving impactful data initiatives within a dynamic and regulated environment.