Senior Data Analyst

TENARAI TECHNOLOGIES PRIVATE LIMITED; Dadri, Pune District, Bengaluru; On-site; INR 900,000 - 1,300,000; Full time

Job summary

TENARAI TECHNOLOGIES PRIVATE LIMITED in India is seeking a Data Analyst to bridge technology and business. You will translate stakeholder needs into analytic requirements, validate AI outputs, and present actionable insights to decision-makers.

You will build dashboards, data models, and automated reports on the Azure platform, collaborate with IT and data engineering, ensure data quality, and mentor junior analysts.

Qualifications

• 5+ years of experience with SQL.
• Experience with Python or R for analytics.
• Strong data modeling, ETL, and analytics frameworks.
• Experience building dashboards and reports with Power BI.
• Ability to translate business questions into analytical frameworks.
• Excellent communication with non-technical stakeholders.

Responsibilities

• Analyze large, complex datasets to identify trends and opportunities.
• Develop and maintain dashboards and automated reports to track performance metrics.
• Translate business questions into analytical frameworks and actionable insights.
• Collaborate with cross-functional teams (business, IT, data engineering) to deliver data solutions.
• Ensure data quality, integrity, and consistency across systems and reports.
• Present findings clearly to non-technical stakeholders and leadership.
• Lead or support advanced analytics initiatives (forecasting, experimentation, performance analysis).
• Mentor junior analysts and promote best practices within the team.

Skills

SQL

Python

Data modeling

ETL processes

Power BI

Stakeholder communication

Tools

Excel

Power BI

Job description

Job Description:

Role Summary

GAPM is establishing a small, cross-functional team to deliver artificial intelligence and digitalization capabilities on a Microsoft Azure platform. The Data Analyst is the bridge between technical delivery and the business: understanding what stakeholders require, shaping requirements, validating that data and artificial‑intelligence outputs are correct and useful, and presenting results in a form that decision-makers can trust.

The post-holder is responsible for transforming complex data into actionable insights that support strategic decision-making. The role acts as a bridge between technical data teams and business stakeholders, ensuring data‑driven improvements in performance, efficiency, and growth

Key Responsibilities

• Analyze large, complex datasets to identify trends, patterns, and business opportunities.
• Develop and maintain data models, dashboards, and automated reports to track performance metrics.
• Translate business questions into analytical frameworks and actionable insights.
• Collaborate with cross-functional teams (business, IT, data engineering) to deliver data solutions.
• Ensure data quality, integrity, and consistency across systems and reports.
• Present findings clearly to non-technical stakeholders and leadership.
• Lead or support advanced analytics initiatives (forecasting, experimentation, performance analysis).
• Mentor junior analysts and promote best practices within the team.

Skills and qualifications:

• Minimum 5 years of experience with SQL.
• Knowledge of statistical analysis and programming languages (Python preferred, R).
• Solid understanding of data modeling, ETL processes, and analytics frameworks.
• Experience performing exploratory data analysis on unfamiliar datasets, including profiling, identifying patterns and anomalies, and forming and testing hypotheses.
• Strong problem‑solving, strong analytical skills, and attention to detail.
• Excellent communication skills for translating data into business insights.
• Proficiency with one data visualization tool, Power BI preferred.
• Demonstrable experience building reports, data models and calculations in Power BI to a professional standard.
• The ability to present data visually in a way that communicates the key message clearly.

Nice to have:

• A background in finance, insurance, or accounting, including an understanding of the associated data and reporting cycles.
• Familiarity with statistical techniques that support robust analysis.
• Familiarity with the behavior of artificial intelligence outputs, so that any assessment of them is informed rather than mechanical.
• Experience working alongside an engineering team in an iterative delivery setting.