Finance Data Analyst / Architect- Senior Associate

Job Summary

A career in our Finance Transformation practice, within Consulting services, will provide the opportunity to work alongside Finance leaders to optimize the structure of their finance functions, re-architect finance processes and implement best-of-breed technology to enable their transformation journey. Join a team of business professionals who work with clients to solve complex problems while utilizing tools to digitally upskill Finance teams. By working with clients to establish and deliver on their transformation roadmap to create value for Finance and beyond. Working in a diverse team, you will help our clients identify process, performance and people and lead the development of meaningful solutions to deliver sustainable change.

Role & responsibilities

• 7-12 years of relevant professional experience, ideally in management consulting or a professional services environment.
• Strong hands-on expertise in financial modeling and data-driven analysis, with experience building models from scratch.
• Hands on experience in deployed curated database, data models and data migration engagements.
• Proficiency with data extraction and transformation tools (e.g., Alteryx or equivalent).
• Strong reporting and data visualization experience (Power BI preferred).
• Proven client-facing experience, including interacting with onshore teams and/or clients and supporting deliverables.
• Strong communication and storytelling skills (written, verbal, and presentation).
• Experience managing complex workstreams in a global delivery model.
• Working knowledge of core finance processes (e.g., AP/AR, Record-to-Report, FP&A) and how data supports finance transformation.
• Ability to align analytical/data models with business rules and data governance standards.
• Strong collaboration skills across geographies and multi-disciplinary teams, with demonstrated coaching/leadership capability.

Preferred candidate profile

• Prior experience in banking or financial services.
• Exposure to data science concepts and advanced analytics.
• Hands-on experience with Python and/or SQL; familiarity with Azure (or similar cloud platforms).
• Experience or applied knowledge of AI/ML use cases in finance or analytics.
• Understanding of enterprise cloud platforms (AWS, GCP, Azure) for data staging, normalization, and transformation.