Position: Data & BI Analyst (Full-Stack)
Location: Bangalore
Work Mode: Hybrid
Min-Max Experience: 4-6 Years
Position Summary:
We are seeking a highly analytical and versatile Senior Data & BI Analyst who 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.
Your Role Responsibilities and Duties:
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.
Backend Querying & Data Engineering (ETL)
- 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.
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.
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 and Qualifications:
Core Technical Skills
- Strong hands-on experience in Data Analytics, Business Intelligence, or Data Engineering roles
- Expert-level proficiency in Tableau and/or Power BI
- Strong command of SQL with experience optimizing complex queries
- Experience with cloud data platforms such as Snowflake, AWS Redshift, or Google BigQuery
- Proficiency in Python for data manipulation, automation, and ETL development
- Experience building and maintaining ETL pipelines and reporting workflows
- Familiarity with distributed data systems and modern analytics architectures
BI & Visualization Skills
- Advanced experience with Tableau calculations, LODs, DAX, parameter actions, and data blending
- Strong understanding of dashboard performance optimization and user experience design
- Ability to create polished, executive-level dashboards with strong design aesthetics
- Experience building scalable reporting frameworks for leadership teams
AI / GenAI Exposure
- Hands-on experience using AI tools such as ChatGPT, Gemini, Claude, or Copilot
- Understanding of AI-assisted analytics workflows and dashboard prototyping
- Exposure to semantic layers, AI-driven data discovery, or intelligent reporting frameworks is a plus
