Top Data Analyst Jobs in Pune

The Data Analyst develops production-grade data and analytics solutions by translating business needs into functional requirements, analyzing and validating data, and contributing to architecture, governance, modeling, quality, engineering, and data science initiatives. The role independently leads solution design and estimation, collaborates with business and technology stakeholders, mentors analysts, and applies SQL, big data, cloud, and data storage expertise to solve complex business problems.

Develops analytics and AI-driven tools for pre-sales value quantification. Manages large datasets using SQL, performs statistical analysis, and creates dashboards in Tableau or Power BI. Builds ROI calculators and web-based solutions, generates actionable insights, and collaborates with Sales, Marketing, Consulting, and Product teams to support customer engagement and strategic decisions.

Performs data profiling, validation, quality testing, anomaly detection, pipeline monitoring, and quality reporting across cloud and on-premises environments. Builds validation rules and data quality artifacts, collaborates with business and technology stakeholders, leads solution design and estimation, and mentors Data Quality Analysts. Works with data lakes, data warehouses, datamarts, and enterprise data platforms.

Manage global product master data using governance standards, workflow tools, mass updates, validation, data cleansing, controls, KPI tracking, and SOP maintenance. Investigate and resolve low- to medium-complexity data issues, support system implementations with ITS, and drive continuous improvement and global standardization. The role requires advanced Excel and SAP skills, product hierarchy experience, and strong knowledge of master data quality practices.

Supports sales-force effectiveness through data cleaning, access governance, KPI reporting, performance trend analysis, and migration from Excel tracking to Power BI dashboards. The role also provides user support, onboarding and training assistance, documentation, process standardization, and continuous improvement across regional sales entities.

Design, clean, analyze, and visualize data using SQL and Python; build Tableau dashboards; apply statistics and basic ML/DS concepts; follow software/data-engineering practices (version control, unit testing, high-performance code); work with structured and unstructured data and cloud environments.

Extracts, transforms, and analyzes media measurement data to identify insights, test hypotheses, and answer client and stakeholder questions. Leads data investigations, develops analytical solutions, supports sales feasibility reviews, and contributes to reporting tools and automation. Collaborates across teams, formulates technical approaches to open-ended problems, and improves analytical workflows using SQL, Python or R, ETL tools, cloud technologies, and Excel.

Analyze and interpret business data, support reporting and insights, and contribute to data-driven decision-making. The role is open to freshers and candidates with up to two years of experience, with opportunities to develop IT and analytical skills.

Analyze operational data and processes, identify bottlenecks, design scalable solutions, automate workflows and reporting with Python and SQL, build dashboards and monitoring, perform root-cause analysis, document logic and collaborate with product, engineering, and ops teams to improve automation and data quality.

Designs and publishes Power BI dashboards and recurring business reports using data from SQL, Azure Data Lake, Snowflake, Excel, and other sources. Creates and optimizes SQL tables, develops calculated fields, monitors data update failures, and resolves root causes. Analyzes data to identify business growth opportunities and collaborates with business leaders to understand reporting needs. Uses SharePoint, PowerApps, and Excel to support reporting workflows.

Prepares and publishes recurring business reports, designs Power BI dashboards, analyzes data for growth opportunities, creates and optimizes SQL tables and queries, monitors data update failures, and collaborates with business leaders to fulfill reporting needs. Uses Azure Data Lake, Snowflake, Excel, SharePoint, and PowerApps while meeting reporting SLAs and supporting business goals.

Analyze courier supply and dispatch operations across onboarding, retention, availability, earnings, assignment, acceptance, and delivery success. Build reliable metrics, dashboards, and self-service reporting; identify root causes of performance changes; evaluate experiments, incentives, and product initiatives; validate data quality; and translate findings into recommendations for product, operations, and leadership.

Analyze structured and unstructured data to identify trends, build dashboards and reports, define KPIs, validate data quality, and provide actionable recommendations. The role requires SQL, BI visualization, Excel, relational database experience, and collaboration with business and technical stakeholders. Preferred skills include Python, ETL and data warehousing, cloud platforms, statistical analysis, forecasting, machine learning concepts, and Agile experience.

Leads a team of scientific data analysts supporting Reaxys, Embase, and future AI-enabled life sciences platforms. Oversees search and API quality, data discoverability, testing, feature releases, quality standards, and customer-focused insights. Uses scientific expertise, Python and Bash scripting, databases, cloud platforms, and AI-enabled testing workflows to improve data integrity and platform performance. Coordinates stakeholders, documents work, presents findings, and drives cross-functional projects.

Leads a team of scientific data analysts supporting Reaxys, Embase, and future AI-enabled life sciences platforms. Oversees search and API quality evaluation, data discoverability, testing, feature releases, customer-focused insights, and quality standards. Uses scientific expertise, data analysis, scripting, databases, cloud platforms, and AI-enabled testing workflows to improve platform reliability and relevance. Coordinates stakeholders, advances projects, documents work, and presents recommendations for product and data improvements.

Own analytics and measurement for HighLevel’s AI product portfolio. Define instrumentation standards, feature-level KPIs, adoption and quality metrics, and rigorous approaches for evaluating nondeterministic AI features. Partner with experimentation leaders, PMs, engineering, and Analytics Engineering to close data gaps, influence product roadmaps, establish canonical metrics, and mentor future analysts.

Business Analyst focused on data engineering and analytics, responsible for requirements gathering, stakeholder management, SQL analysis, data profiling, quality validation, reconciliation, reporting, and documentation. The role requires understanding ETL/ELT, pipelines, data warehousing, data modeling, databases, and Agile delivery. Experience with Python, PySpark, Airflow, cloud data platforms, APIs, and AI/ML data use cases is advantageous.

Analyzes and develops software applications across the full development lifecycle, including requirements gathering, technical design, coding, testing, troubleshooting, documentation, deployment, and support. Collaborates with solution architects, project leads, and client teams while following Agile/Scrum practices. Requires strong debugging, problem-solving, communication, consulting, and independent-working skills, plus a bachelor's degree in a relevant technical field.

Provides research and data-analysis support to economists focused on monetary economics and financial markets in Asia and the Pacific. Responsibilities include preparing publications and presentations, collecting and validating data, reviewing methodologies, developing databases, identifying new data sources, applying advanced analytics, and collaborating on innovation projects. The role bridges economics, data, and technology in a multicultural international environment.

Supports liquidity regulatory reporting controls by documenting data flows, business data elements, lineage, transformations, and controls from booking systems to reporting platforms. Performs SQL-based data analysis, test-case development, functional and business testing, quality remediation, root-cause analysis, requirements management, stakeholder coordination, and management reporting. Contributes to implementation activities, change control, documentation standards, and training junior team members.

Supports hosted e-discovery platforms by loading and transforming data, creating databases and user accounts, configuring permissions, investigating client technical inquiries, and assisting customers through phone, email, and screen sharing. The role also manages internal service-level tasks, collaborates with Engineering, IT, Application, and Project Management teams, and provides platform walkthroughs when needed.

Maintains taxonomies, business glossaries, classification hierarchies, metadata, and testable data rules in a governance platform. Analyzes rule libraries for conflicts, duplicates, and coverage gaps; supports reference data certification, request triage, documentation, governance reporting, and stakeholder enablement. The role ensures governed artifacts are accurate, traceable, auditable, and operationalized across data quality and classification workflows.

Own marketing database operations for EMEA, including audience segmentation, data quality, privacy compliance, and performance analysis. Translate complex marketing data into actionable insights, recurring reports, and segmentation models. Partner with Marketing Operations, IT, and Data teams to improve database accuracy and processes, while enabling stakeholders through clear communication and training. The role requires strong SQL, marketing technology, project ownership, and business-facing analytical skills.

Conduct a three-hour interactive online training session on qualitative data analysis, including thematic and content analysis, coding, codebook development, identifying themes, transcript and focus group analysis, practical case studies, and qualitative analysis tools.

Build, maintain, and optimize scalable data pipelines supporting marketing analytics, campaign measurement, brand research, customer segmentation, and insights. Process large datasets, implement data quality controls, resolve systemic errors, support data governance, document data sources, manage production releases, and collaborate with marketing, analytics, technology, and business stakeholders. The role also supports semantic data layers and responsible AI data preparation.