ROLE PURPOSE A finance-literate senior analyst who turns large, multi-source data into clear financial and operational insight. Sitting within D&A; and partnering the Strategy & Business Performance team, the role owns the analysis, dashboards and reporting that help internal and external clients — and Tag's own Finance and Operations leaders — understand performance and make better commercial decisions. The emphasis is on the “so what”: telling the story behind the numbers, with particular weight on financial outcomes.
KEY RESPONSIBILITIES
Financial & Commercial Analytics (primary focus)
• Build and maintain financial and operational reporting — revenue, cost, margin, utilisation and P&L; views — for business partners and the Finance / Operations In-charge.
• Support FP&A; activity: budgeting, forecasting, re-forecasting, and scenario / what-if modelling.
• Run variance analysis (actuals vs. budget, forecast and prior period) and explain the drivers in plain language.
• Translate commercial questions (“why did margin move?”) into structured analysis and clear recommendations for executive leaders and business partners. Data Analysis & Modelling
• Analyse business requirements and translate them into insight through effective reporting and analysis.
• Apply statistical data analysis and build models that hold up to scrutiny. Data Extraction & Integration
• Extract data from multiple sources — databases and spreadsheets — using Excel, DOMO and SQL.
• Develop and maintain ETL (Extract, Transform, Load) workflows to automate loading and keep Excel and DOMO in sync. Data Transformation & Preparation
• Implement data cleansing, transformation and validation so outputs are accurate and consistent.
• Use DOMO's data-preparation and transformation capabilities to prepare data for analysis and reporting. Data Visualisation & Storytelling
• Create compelling, insightful dashboards, charts and graphs in DOMO, Power BI, Tableau and Excel.
• Apply data-visualisation best practice so the “so what” is obvious; design self-service reporting solutions with stakeholders. Automation & Efficiency
• Automate repetitive tasks and reporting using macros, VBA, Power Query, calculations and data models.
• Build reusable templates, standardised processes and components to lift BI productivity. Data Governance, Quality & Security
• Maintain a high level of attention to detail around QA and cleansing of large data sets.
• Help implement data governance — access controls, user roles / permissions and data-security measures that protect integrity and confidentiality. Collaboration, Stakeholder Management & Documentation
• Partner cross-functional teams — Finance, Operations, Project Managers, data engineers and department heads — to understand requirements and deliver effective BI.
• Present insights back to executive leaders / business partners to drive strategic improvement.
• Document data models, workflows and processes to support knowledge transfer and future enhancements. TECHNICAL SKILLS Must-have (core) BI & visualisation: DOMO, Power BI, Tableau Spreadsheets:
Advanced MS Excel — PivotTables, VLOOKUP / XLOOKUP, advanced formulas, Power Query Automation: VBA / macros, Power Query, reusable data models Data prep & querying: ETL workflows, data cleansing & validation, SQL Financial reporting: Financial & operational reporting, FP&A; concepts, forecasting, variance analysis Analysis: Statistical data analysis
• Experience with data management, cleansing, wrangling, integration and automation.
• A track record of finding actionable insights and “joining the dots” in data.
• Experience building real-time dashboards across a range of data sets; DOMO visualisation a plus. Solid plus Modelling: Power BI data modelling (DAX); real-time dashboarding across diverse data sets Finance systems: Exposure to ERP / financial-planning tools (e.g., SAP, Oracle / Hyperion, Anaplan, Workday Adaptive, NetSuite) Technical edge: Programming / scripting — JavaScript or HTML/CSS; Python Nice-to-have CRM data: Salesforce, HubSpot or Zoho Domain: Creative-production / media-agency or shared-services finance environment EXPERIENCE
• 5–8 years in data analytics / business intelligence, with a substantial finance or commercial-reporting component.
• 3–5 years with comparable finance-analytics exposure.
• Finance background required — e.g., FP&A;, management / commercial reporting, or finance business-partnering — alongside hands-on BI delivery. EDUCATION
• Bachelor’s degree in finance, Accounting, Economics, Commerce, Data Science, Statistics, Engineering or a related field (or equivalent work experience).
• A finance qualification is a strong advantage — e.g., MBA (Finance), CA / CMA (or inter), or CFA progress.
📌 Senior Data Analyst (Bengaluru)
🏢 Tag
📍 Bengaluru