Financial Data Analyst

We are at Tech Mahindra, Year on Year we are growing rapidly. To maintain this we’re seeking savvy, motivated Data Analyst to join our world class Business Finance network.
As a Data analyst you will be focused on working collaboratively with senior management & team within Business Finance. Using BI tools, data models &, process created to present analysed data for both internal & external team within Business. This position will act as hub of information within the Business Finance team, who translates the raw data into valuable business insights to draw business decisions.

Responsibilities:

• Lead & execute complex data queries from large databases & related analytics to drive business decisions
• You’ll use your expertise in the collection, analysis and management of quantitative financial data, as you create meaningful reports 
• Lead the development of all weekly and monthly financial metrics, alongside all financial planning and, reporting models
• Power queries & combine data from variety of sources for use in reporting, research &, decision making
• Responsible for the quality & completeness of data queried from various system within the eco systems by performing & overseeing the auditing of data
• Execute & Manage the completion of large reconciliation tasks & analytics
• Implement improved reporting & data workflows processes
• As an analyst, you’re a quick thinker: able to manage competing priorities while providing level-headed guidance, even during unexpected events

Skills:

• Good team player, developing and obtaining Knowledge from cross functional teams on process & structures along with good reporting and analytical skills
• Innovative thinker – ideas to increase efficiencies and optimise reporting processes
• Commercial and economic awareness, including an awareness of economic factors that can influence the IT Outsourcing, is important.
• Good interpersonal skills to coordinate with internal stakeholders

Technical:

• Experience in working on BI tools (i.e. Qlik Sense, Power BI etc.)
• Advance user of Microsoft office suit (Excel, Word, PowerPoint)
• Strong knowledge on statistical packages for analyzing large datasets (SAS, Excel, SPSS, etc.)