Lead Business Analyst – Financial Systems & Data Platforms

Intellibus is a company focused on engineering platforms that impact billions of lives globally. They are seeking a Principal/Senior Consulting Business Analyst to lead complex transformation initiatives for large financial services platforms, acting as a trusted advisor and driving alignment across various teams.

Responsibilities:

• Lead business analysis and data strategy across large, multi-team financial platform initiatives
• Partner with client executives, product owners, and engineering leadership to define end-to-end solution scope
• Own complex data mapping, transformation logic, and validation strategy across systems
• Translate regulatory, operational, and product needs into technical execution plans
• Drive prioritization and trade-off decisions across business and technology stakeholders
• Establish governance around requirements, data quality, and delivery milestones
• Lead cross-functional workshops with senior business, compliance, and technology teams
• Mentor junior analysts and set standards for business analysis excellence
• Act as escalation point for data and integration risks impacting business delivery
• Represent Intellibus as a senior consulting leader embedded within client programs

Requirements:

• Education: Bachelor's or Master's in Engineering, Computer Science, or related field
• 15+ years of experience leading business analysis and data transformation initiatives in financial services
• Proven experience working in consulting or advisory environments serving large enterprise financial platforms
• Strong background in banking, capital markets, mortgage, payments, or regulatory data systems
• Demonstrated ability to lead complex, multi-stakeholder programs
• Strong technical fluency with data platforms, integration architectures, and system design
• Ability to communicate effectively with executive, product, compliance, and engineering audiences
• Comfortable making decisions in ambiguous, high-pressure delivery environments
• Financial data models: transactions, positions, balances, reference data
• Source-to-target mapping and data lineage
• SQL and data validation techniques
• ETL and event-driven data pipelines
• APIs and service-oriented architectures
• Regulatory and operational reporting workflows
• Agile delivery at enterprise scale