About the role

We are looking for a highly analytical, business-oriented Data Analyst to lead our analytics function and turn complex data into decisions leaders can act on. You will own the organisation's KPI/KRA framework, build executive dashboards in Power BI, run advanced analytics in Python and SQL, and apply Generative AI to automate reporting and surface insight faster.

As a Team Lead, you will partner with business leaders, product managers, operations and senior management to support strategic decision-making, while mentoring junior analysts and raising the bar on analytics best practices.

Key responsibilities

Business analytics

- Analyse large volumes of structured and unstructured data to identify trends, patterns, opportunities and business rismoks.
- Convert business requirements into analytical solutions and measurable outcomes.
- Prepare executive-level MIS reports and business-performance dashboards.
- Perform root cause analysis (RCA) and recommend corrective actions.

KPI / KRA management

- Design, implement and monitor organisation-wide KPIs and KRAs.
- Define business metrics across Sales, Operations, HR, Finance, Customer Success and Product.
- Build automated KPI-tracking dashboards and conduct periodic performance reviews.
- Identify performance gaps and provide actionable recommendations.

Dashboard development

- Design and develop interactive, drill-down executive dashboards in Microsoft Power BI.
- Optimise data models for performance and scalability.
- Implement Row-Level Security (RLS) where required.
- Publish and maintain reports in the Power BI Service.

Data analysis & automation

- Build reusable Python scripts for data cleaning, transformation, statistical analysis, forecasting,



validation and automated report generation.
- Automate repetitive analytical tasks and reduce reporting turnaround time.
- Perform ad hoc analysis to support time-sensitive business decisions.

SQL & database management

- Write and optimise complex SQL queries for data extraction and reporting.
- Work with relational databases such as MySQL, PostgreSQL, SQL Server or Amazon RDS.
- Create views, stored procedures and analytical datasets.

Generative AI & AI-assisted analytics

- Use LLMs for data summarisation, insight generation, SQL generation, documentation and interpretation.
- Build AI-assisted analytics workflows using modern AI platforms and APIs.
- Evaluate and integrate AI tools to enhance reporting and decision support.

Data quality & governance

- Ensure data accuracy, consistency and completeness; define data-validation rules.
- Maintain metadata and documentation.
- Collaborate with engineering teams to continuously improve data quality.

Stakeholder management & leadership

- Engage senior leadership to understand objectives and translate business questions into analytical solutions.
- Present findings clearly to both technical and non-technical audiences.
- Mentor junior analysts and champion analytics best practices across teams.

Qualifications & experience

Education





- Bachelor's degree in Computer Science, IT, Statistics, Mathematics, Engineering, Business Analytics or a related field.
- Master's degree in a related field preferred.

Experience

- 4-6 years in Data Analytics or Business Analytics.
- Proven experience designing KPI/KRA frameworks.
- Hands-on Power BI dashboard development.
- Strong Python programming and advanced SQL proficiency.
- Experience working with enterprise-scale datasets.
- Experience using Generative AI tools in professional workflows.

Preferred skills

- Excellent analytical, problem-solving and communication skills.
- Understanding of business processes and performance management.
- Knowledge of ETL processes and data-warehousing concepts.
- Experience with data governance and master data management.
- Familiarity with Agile/Scrum methodologies.
- Ability to manage multiple projects and deadlines.
- Robust documentation and process-improvement skills.

Key competencies

Critical Thinking • Business Acumen • Data Storytelling • Strategic Analysis • Decision Support • Stakeholder Management • Attention to Detail • Leadership & Mentoring • Time Management • Innovation & Continuous Learning

How success is measured

- Accuracy and reliability of reports.
- Timely delivery of dashboards and analytical insights.
- Automation of manual reporting processes and reduced turnaround time.
- Improvement in business KPIs through data-driven recommendations.
- Adoption of dashboards across business functions.
- Measurable data-quality improvements.
- Stakeholder satisfaction.
- Effective use of AI tools to enhance productivity and decision-making.

📌 Senior Data Analyst (Uttar Pradesh)
🏢 Buddy4Study
📍 Uttar Pradesh