Role Overview

The Senior Data Analyst will lead complex analytical initiatives and convert sales, production, inventory, supply-chain, finance, customer and market data into decision-ready insights. The role will own critical dashboards and KPI definitions, strengthen data quality and reporting standards, partner with senior stakeholders, and guide junior analysts. The successful candidate will combine robust technical execution with commercial understanding and clear data storytelling.

Key Responsibilities

- Lead end-to-end analytics projects, from business requirement gathering and solution design through validation, deployment and performance monitoring.
- Analyze complex datasets to identify business drivers, trends, risks, root causes and growth opportunities.
- Design, develop and maintain scalable Power BI dashboards, executive reports and self-service analytics solutions.
- Define, standardize and govern KPIs across sales, dealer or distributor performance, product movement, inventory, production, procurement, logistics and finance.
- Build and optimize advanced SQL queries, reusable datasets, data models and transformation logic for reliable reporting.
- Hands on experience of working with Databricks and writing optimal scripts
- Lead demand forecasting, sales planning, inventory analysis, stock ageing, variance analysis and scenario modelling.
- Evaluate regional, product, site, customer, and channel performance and recommend measurable actions to management.
- Establish data-quality checks, reconciliation controls, documentation, lineage and access standards.
- Automate recurring reports and analytical workflows using Power Query, Python or other appropriate tools.
- Translate ambiguous business questions into analytical approaches, measurable metrics and clear recommendations.
- Present insights and data stories to senior management and cross-functional stakeholders in an accessible, decision-focused format.
- Partner with sales, marketing, production, supply chain, finance,



IT and field teams to improve data availability and adoption.
- Monitor dashboard performance, refresh reliability, query efficiency and user experience, and resolve reporting issues.
- Support data governance, master-data consistency and responsible handling of confidential business information.
- Review the work of junior analysts, provide technical guidance and promote best practices in SQL, Databricks, data modelling, visualization and documentation.
- Stay current with analytical tools and identify opportunities to improve the organizations reporting and decision-making capabilities.

Qualifications and Experience

- Bachelors or master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Commerce or a related quantitative discipline.
- 4–6 years of relevant experience in data analytics, business intelligence, management reporting or decision support.
- Demonstrated experience independently delivering dashboards and analytical projects for business stakeholders.
- Experience working with large, multi-source datasets and resolving data-quality or reconciliation issues.
- Experience in manufacturing, agriculture, fertilizers, micronutrients, distribution, sales operations or supply chain is strongly preferred.

Technical Skills

- SQL: Advanced querying, joins, subqueries, common table expressions, window functions, aggregations and query optimization.
- Power BI: Data modelling, DAX, Power Query, interactive dashboards, row-level security, publishing and refresh management.
- Databricks: Strong hands-on experience with Databricks SQL,



building and querying Delta Lake tables; using Python/PySpark and Spark SQL for data preparation and transformation; scheduling and monitoring jobs and workflows; and optimizing queries, compute usage and data pipelines for performance and cost.
- Microsoft Excel: Advanced formulas, PivotTables, Power Query, charts, scenario analysis and reporting automation.
- Analytics: Statistical analysis, segmentation, trend and variance analysis, forecasting and performance measurement.
- Programming: Working knowledge of Python or R for data preparation, automation and analysis.
- Data practices: ETL concepts, dimensional modelling, data validation, KPI governance, documentation and data lineage.
- Preferred: Exposure to ERP or CRM systems, cloud data platforms, Microsoft Fabric, Azure, Tableau or similar technologies.

Core Competencies

- Strong analytical judgment and structured problem-solving.
- Business acumen and the ability to connect analysis with commercial and operational outcomes.
- Excellent stakeholder management, communication and presentation skills.
- Ability to lead projects, prioritize competing requests and meet deadlines independently.
- High attention to detail and commitment to data accuracy and confidentiality.
- Ability to coach colleagues and provide constructive technical guidance.
- Curiosity, ownership and a continuous-improvement mindset.

Key Success Measures

- Accuracy, reliability and timely delivery of executive reports and dashboards.
- Adoption of standardized KPIs and self-service analytics across business teams.
- Reduction in manual reporting effort, data discrepancies and dashboard refresh issues.
- Quality and business impact of analytical recommendations.
- Improvement in forecasting, inventory visibility and operational decision-making.
- Successful delivery of analytics projects within agreed scope and timelines.
- Development and improved capability of junior analysts.

📌 Senior Data Analyst (Karnataka)
🏢 DhishaAI Complete Analytics
📍 Karnataka