Senior Data Analyst

Role Objective We are seeking a highly analytical and versatile Senior Data & BI Analyst to join our Enterprise Technology Group. This is not a pure front-end visualization role. The ideal candidate will operate as a "full-stack" analyst—taking full ownership of the data pipeline from backend querying and ETL processes, to deep-dive business analysis, and finally, developing executive-ready dashboards in Tableau, Power BI, SAP SAC, Looker etc. Additionally, this role requires a forward-thinking approach, utilizing GenAI and LLM tools to rapidly prototype data solutions before moving them to production. Key Responsibilities 1. End-to-End Dashboarding & Visualization (Primary) Design, build, enhance and run & maintain complex, interactive, and highly optimized dashboards in Tableau , Power BI , SAP SAC, Looker, etc. Translate business requirements into compelling visual narratives that drive executive decision-making. Develop intuitive, interactive dashboards focused on visually appealing data storytelling to guide stakeholders from high-level trends down to actionable root causes Drill down capability for all reports and dashboard should be in-built – e.g. one can start with India and then create a regional or multi region cohort of our viewers for a program or for a genre Build, Maintain, Enhance device agnostic Desktop, Tablet and Mobile friendly dashboards Manage the administration, access control, and performance tuning of existing dashboards to ensure zero downtime and optimal load speeds. 2. Backend Querying & Data Engineering (ETL) (Secondary) Write advanced, highly optimized SQL queries to extract, transform, and load (ETL) data from various databases and data warehouses. Build and maintain robust data models that seamlessly connect backend architecture to front-end BI tools. Troubleshoot data discrepancies, optimize query performance, and ensure data integrity across all reporting layers. 3. Deep-Dive Analysis & Business Intelligence (Primary) Go beyond simply reporting numbers to actively uncover trends, anomalies, and actionable business insights. Conduct ad-hoc deep-dive analyses to answer complex business questions, acting as a strategic partner to internal stakeholders. Present findings clearly to non-technical business leaders, bridging the gap between raw data and business strategy. 4. GenAI Prototyping & Innovation (Primary) Leverage GenAI and Large Language Models (LLMs) to quickly build Proof of Concepts (POCs) for new dashboards, metrics, and analytical frameworks. Translate successful GenAI-driven mockups and insights into fully functional, scalable production dashboards in Tableau/Power BI/SAP SAC/Looker etc. Deploy the use of AI tools to faster pipeline development, data lineage, creation of semantic layer and any data cleaning, as needed Stay updated on the latest AI-driven analytics trends to continuously improve the team's efficiency and output quality. Required Skills & Qualifications Experience: 4 to 6 years of hands-on experience in Data Analytics, Business Intelligence, or Data Engineering. BI Tools: Expert-level proficiency in Tableau and Power BI, ( SAP SAC, Looker optional can be learned on the job ) including advanced calculations (LODs, DAX), parameter actions, and data blending. Database & Querying: Strong command of SQL. Experience with cloud data platforms (e.g., AWS Redshift, Snowflake, or Google BigQuery) and relational databases. ETL/Scripting: Proven ability to build and manage ETL pipelines. Proficiency in Python for data manipulation and Airflow jobs. GenAI Aptitude: Experience using AI tools (ChatGPT, Gemini, Copilot, Claude, etc.) for data querying, code generation, or rapid dashboard prototyping. And converting the aligned format into a working real-world project. Soft Skills: Exceptional problem-solving abilities, strong business acumen, and the capability to work independently with minimal supervision. Extreme attention to detail and experience building highly polished dashboards for senior leadership/C-suite and having an eye for good design aesthetics Background - Computer Engineering