Top Data Analyst Jobs in Pune

Perform business process mapping and requirements elicitation (BPMN 2.0), design 'To be' solutions, produce BRDs, use cases, user journeys and acceptance criteria, support TOM and foundation data initiatives, drive process improvements using Lean/Six Sigma, document processes, conduct training, and collaborate with stakeholders to translate business needs into application and operational requirements.

Creates, updates, and maintains material master data and parts records in SAP and IFS. Collaborates with BOM, procurement, engineering, manufacturing, and compliance teams to collect and validate information. Reviews data quality, resolves inconsistencies, maintains documentation, monitors KPIs and SLAs, ensures turnaround-time compliance, and identifies process improvements while supporting regulatory and company data standards.

Supports EDI configuration and business processes for North American sales organizations. Monitors and troubleshoots inbound and outbound transactions, maps data between internal systems and standardized EDI formats, manages access, and ensures compliance with industry rules. The role reports EDI KPIs, maintains process documentation, analyzes customer requirements, and applies Lean continuous-improvement methods to reduce errors and improve touchless order flow.

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.

Build and maintain data validation rules, test cases, quality artifacts, profiling processes, anomaly detection, and quality reports. Perform data quality checks across testing lifecycle stages and collaborate with business, technology, operations, governance, architecture, engineering, and analytics teams. Lead solution design and estimations, work across cloud and on-premises data environments, and mentor Data Quality Analysts.

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.

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.

Entry-level Product Data Analyst internship supporting product analytics: build and analyze conversion funnels, evaluate A/B tests, create dashboards, respond to ad-hoc data requests, write SQL pipelines, monitor data quality, and translate findings into visual summaries to inform product decisions.

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.

Internship data analyst supporting dashboard monitoring, user behavior and content ecosystem analysis, A/B test evaluation, campaign performance analysis, data quality assurance, and metric documentation. The role uses SQL and Excel to derive insights on engagement, retention, conversion, and creator ecosystems, while collaborating with product and operations teams in a blockchain and digital assets environment.

Provides L1 production support for financial applications and enterprise data platforms. Responsibilities include monitoring ETL jobs, data pipelines, batch schedules, alerts, and incidents; troubleshooting data quality, reconciliation, ingestion, reporting, and application issues; performing SQL-based data updates, smoke testing, root-cause analysis, and impact assessment; coordinating with technical and business teams; escalating complex issues; supporting disaster recovery, audits, automation, and continuous service improvement.

Design and independently deliver data analytics projects, using advanced statistical and programming techniques across complex data sources. Develop scalable solutions, visualize and communicate findings, recommend business actions, and influence implementation. Lead junior analysts, collaborate with technical and nontechnical stakeholders, explore data monetization opportunities, and ensure compliant use of data assets through governance partnerships.

Support Finance and Central Operations by building dashboards, reporting, automated data pipelines, reconciliations, controls, and analytics. Analyze revenue, expenses, margins, cash flows, payment volumes, disputes, exceptions, and processing performance. Partner with Finance and Payment Operations to investigate discrepancies, automate workflows, improve data quality, and translate business questions into reliable models and actionable insights.

Develop and deliver AI/ML solutions by building supervised and unsupervised models, deep learning systems, NLP and LLM applications. Responsibilities include LLM fine-tuning, prompt engineering, RAG, vector databases, transformer architectures, and AI agent deployment. The role requires partnering with business stakeholders, presenting technical findings, and continuously learning emerging AI technologies.

Build and maintain internal business intelligence dashboards covering revenue, profitability, headcount costs, and team utilization. Support leadership, Finance, and HR with ad hoc analysis and planning insights. Maintain data hygiene and a single source of truth for business metrics, translating raw data into clear recommendations.

Audits and validates labeling annotation data for accuracy, consistency, guideline adherence, and regulatory compliance. Identifies errors and root causes, monitors quality KPIs, leads governance cycles, translates data trends into process improvements, and leads the NC Program. Collaborates with agencies and internal stakeholders across labeling operations.

Develop and maintain interactive Tableau dashboards and reports that turn complex data into actionable business insights. Extract, transform, and analyze data from multiple sources using SQL, identify trends, troubleshoot data issues, and support data visualization best practices. Collaborate with business stakeholders to translate analytical needs into clear visual solutions and recommendations for nontechnical audiences.

Supports data engineering initiatives that make raw data usable and accessible. Works on moderately complex projects, applies technical concepts to identify solutions, resolves technical issues, and contributes to data acquisition, integration, provisioning, analytics platforms, and business intelligence capabilities.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Analyze large-scale datasets to generate actionable business insights, define and monitor KPIs, build dashboards and automated reports, maintain data pipelines, and investigate anomalies across ad delivery, bidding, monetization, campaigns, traffic quality, and platform performance. Collaborate with product, engineering, operations, and business teams to support strategic and real-time decisions.

Gather, clean, and analyze data from multiple sources; build and maintain Power BI and Excel dashboards; run SQL queries and Python scripts for automation; collaborate with cross-functional teams to interpret trends and communicate insights; create documentation and improve reporting processes.

Perform exploratory analysis, build dashboards and reports (Tableau), write SQL queries, use Python for data cleaning and predictive models, collaborate with stakeholders, communicate insights, and maintain data models, pipelines, and quality checks.

Extracts, analyzes, validates, and abstracts clinical data from EHR/EMR systems for registries, reporting, and quality improvement programs. Reviews pathology, radiology, and treatment reports; maintains high accuracy and inter-rater reliability; protects patient confidentiality under HIPAA; prepares reports; and supports quality assurance activities. Requires advanced medical terminology knowledge, clinical data expertise, attention to detail, and independent work capabilities.