Job Title:  Technology & Transformation - Engineering - Senior Consultant - Data Analyst - Pune

The Team

Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning.

Your work profile

The Data Analyst is responsible for analysing large datasets, generating actionable insights, and supporting business decision-making through dashboards, reports and deep-dive analysis.

This role requires strong analytical thinking, SQL expertise and the ability to translate business questions into data-driven insights, metrics, business rules and analytical views that support business, product and data product initiatives.

Data Analysis & Insight Generation

• Analyse structured and semi-structured data to identify trends, patterns and actionable insights.
• Conduct ad-hoc analysis and present findings in a clear, concise and business-friendly manner.
• Translate business questions into analytical approaches, datasets, KPIs and measurable insights.
• Support dashboard, reporting and deep-dive analysis requirements for business and product stakeholders.
• Document analysis, assumptions, definitions and business rules for transparency, consistency and reusability.

SQL, Data Validation & Stakeholder Collaboration

• Write efficient SQL queries to extract, transform and analyse data from multiple sources.
• Perform data validation, reconciliation and quality checks to ensure accuracy, completeness and consistency.
• Partner with business, product and data engineering teams to understand requirements and define KPIs.
• Support data product initiatives by defining metrics, business rules and analytical views.
• Work with data engineering teams to validate source-to-report data flows and resolve data discrepancies.

Key skills required:

• Advanced SQL skills including querying, joins, aggregations, window functions and common table expressions.
• Strong data analysis skills with ability to identify trends, patterns, outliers and business insights from large datasets.
• Hands-on experience with Excel including advanced formulas, pivot tables, data modelling and analytical reporting.
• Experience working with structured and semi-structured data across multiple business and technology sources.
• Experience working with data lakes, data warehouses, AWS data services or Databricks.
• Ability to define KPIs, business rules, metrics and analytical views for reporting and data product use cases.
• Strong understanding of data validation, reconciliation, quality checks and data consistency practices.
• Ability to conduct ad-hoc analysis and communicate insights clearly to business and technical stakeholders.
• Strong documentation discipline to capture assumptions, definitions, logic and analysis outcomes for reusability.

Key Skills & Competencies

• Core skills: Data analysis, SQL, KPI definition, reporting analysis, business rule definition and insight generation.
• SQL expertise: Advanced querying, joins, window functions, common table expressions, aggregations and data transformation logic.
• Excel skills: Advanced formulas, pivot tables, data modelling, reconciliation and analytical summaries.
• Data platform exposure: AWS data services, Databricks, data lakes and data warehouses.
• Data quality mindset with experience in validation, reconciliation, accuracy checks and consistency checks.
• Analytical thinking and problem-solving skills with ability to convert business questions into data-driven insights.
• Stakeholder collaboration with business, product and data engineering teams to align on requirements and KPIs.
• Ability to prepare clear documentation of definitions, assumptions, analytical logic and findings.
• Strong communication skills with ability to present insights in a concise and actionable manner.
• Proficiency in English is required.

Success Metrics

• Accurate, timely and actionable insights delivered to support business decision-making.
• High-quality SQL analysis, dashboards, reports and analytical views aligned to stakeholder requirements.
• Improved data trust through effective validation, reconciliation and quality checks.
• Clear KPI definitions, business rules and documentation adopted across reporting and data product initiatives.
• Positive stakeholder feedback on analysis quality, clarity of findings and business relevance.
• Reusable analytical documentation that improves transparency, consistency and future analysis efficiency.

Location and Way of Working:

Base location: Pune / Bengaluru