Finance Commercial Lead

Project Role : Finance Commercial Lead Project Role Description : Oversee commercial relationships with a client to optimize financial and business operations results and deliver client value. Work closely with business leads to drive financial performance, understand and mitigate business risks, manage investments and accountability, and provide guidance to the team. Must have skills : Data Engineering Good to have skills : NA Minimum 3 year(s) of experience is required Educational Qualification : 15 years full time education

Summary:

As a Finance Commercial Lead, a typical day involves managing and nurturing commercial relationships with clients to enhance financial and business outcomes. This role requires close collaboration with business leaders to steer financial performance, identify and address potential business risks, oversee investment management, and ensure accountability. Additionally, the position involves providing strategic guidance and support to the team to align efforts with client objectives and deliver measurable value.

Roles & Responsibilities:

• Expected to perform independently and become an SME.
• Required active participation/contribution in team discussions.
• Contribute in providing solutions to work related problems.
• Collaborate with cross-functional teams to align commercial strategies with overall business goals.
• Monitor and analyze financial data to identify trends and opportunities for improvement.
• Support the development and implementation of financial plans and budgets.
• Assist in preparing reports and presentations for stakeholders to communicate commercial insights and progress.
• Mentor junior team members to foster professional growth and knowledge sharing.

Professional & Technical Skills:

• Must To Have Skills: Proficiency in Data Engineering.
• Strong knowledge of data integration, data warehousing, and data pipeline development.
• Experience with cloud platforms and big data technologies to manage large-scale financial datasets.
• Ability to design and optimize data architectures to support business intelligence and analytics.
• Familiarity with programming languages commonly used in data engineering such as Python or SQL.