Top Data Analyst Jobs in Bangalore

Own analytics for Words With Friends Instant, providing insights on player behavior, product performance, experimentation, revenue, retention, and engagement. Design statistical experiments, dashboards, telemetry, and ETL pipelines; analyze trends and feature health; maintain data tools and models; and communicate recommendations to product, engineering, design, and executive stakeholders. The role also supports AI initiatives and optimization of the player experience.

Analyze product performance, user behavior, funnels, cohorts, retention, LTV, and experimentation results to guide product decisions. Build dashboards, reports, data marts, dimensional models, and semantic layers for self-service analytics. Partner with Product, Engineering, Marketing, and Business teams to define KPIs, identify growth opportunities, improve engagement, and support monetization. Use SQL, Python, BI tools, and AI-assisted workflows to deliver accurate, actionable insights.

Analyze large player datasets to identify opportunities, improve game metrics, and support evidence-based decisions. Build dashboards and maintain trusted data sources, communicate insights to technical and non-technical stakeholders, and collaborate with product, design, and engineering teams. Design, test, verify, and help deploy machine learning models and product features at scale. Deliver impactful analytics and data science projects aligned with product roadmaps.

Maintain and govern global master data across supply chain systems, ensuring quality, consistency, compliance, and traceability. Perform data validation, cleanup, reviews, KPI monitoring, root-cause analysis, and corrective actions. Support migrations, testing, and post-go-live operations while collaborating cross-functionally. Improve and automate master data processes, maintain documentation, and provide user training. The role requires strong Excel and reporting skills, SCM process knowledge, ERP exposure, and effective global stakeholder collaboration.

Develop and maintain Power BI dashboards, reports, data models, and refresh processes. Write and optimize SQL queries, perform data validation and quality checks, and collaborate with IT and data engineering teams. Translate stakeholder requirements into reporting solutions, maintain documentation, follow reporting standards, and deliver work within project timelines.

Analyze and interpret large healthcare datasets, build and maintain data pipelines and structures, collaborate with cross-functional teams to deliver actionable insights, and document data processes and analyses.

Monitor and triage enterprise data pipeline incidents, investigate root causes, assess downstream impact, and coordinate escalations through resolution. Administer the Pantomath data observability platform, configure monitors and alerts, onboard pipelines, maintain integrations, and reduce alert noise. Communicate outage status and resolution timelines to stakeholders, document incidents and RCAs, support post-incident reviews, and conduct shift handoffs within a shift-based operations model.

Leads data strategy, governance, ETL pipelines, AI-assisted analytics, knowledge management, decision modeling, simulations, and executive reporting for retail selection, pricing, and inventory optimization. Builds reliable datasets and self-service dashboards, trains business users, applies prompt engineering and generative AI, and mentors analysts. Requires advanced SQL, Python or R, visualization, communication, and data storytelling skills, with preferred experience in GitHub, Airflow, knowledge bases, retail, demand forecasting, statistics, and machine learning.

Build and maintain scalable ELT/ETL pipelines for high-frequency power system data, automate simulation-result extraction with Python, manage PostgreSQL schemas and data-lake architectures, and create Power BI or Tableau dashboards. The role partners with power systems engineers to connect simulation outputs with grid reliability and economic insights. It also supports data modeling, warehousing, business intelligence, cloud data environments, and internal data-driven initiatives.

Own sales and growth data pipelines, maintain daily reporting, coordinate performance updates across content and growth teams, and identify trends, risks, and operational gaps. Analyze ambiguous business questions using SQL, analytics, and AI-assisted workflows. Build dashboards, reporting systems, and automated analytical pipelines while ensuring data accuracy and supporting leadership and cross-functional stakeholders with timely business intelligence.

Leads economic modeling, traffic due diligence, toll revenue forecasting, econometric and time-series analysis, ETL architecture, data validation, and commercial recommendations. Presents findings to senior clients and investment committees, coordinates with traffic engineering teams, mentors analysts, manages project teams, and supports business development. Requires advanced Python, SQL, Excel, cloud analytics, reproducible data pipelines, and expertise in transport analytics and investment-grade modeling.

Analyze large healthcare datasets to extract insights, build data models, reports and dashboards, ensure data quality, collaborate with cross-functional teams, and present findings to stakeholders.

Collect, clean, transform, and analyze data to identify actionable insights and trends. Create Power BI or Tableau dashboards, prepare reports, present findings, and support data-driven decisions across Product, Marketing, and Sales teams. Collaborate with technical teams to maintain data integrity and quality.

Analyze data, interpret results, and produce reports, KPI dashboards, and visualizations to support data-backed decisions. The role involves acquiring and maintaining data, collaborating with departments on analytics needs, identifying meaningful insights, and applying statistical techniques such as A/B testing, ANOVA, probability distributions, and regression analysis. Candidates should have strong analytical, communication, database, and data modeling skills.

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.

Leads enterprise data engineering, warehousing, analytics, reporting, and regulatory data initiatives for banking and financial services. Designs data platforms and pipelines, develops Oracle SQL and PL/SQL solutions, builds dashboards and reporting frameworks, and ensures data quality, governance, reconciliation, and lineage. Supports lending, risk, securities, tax, payments, treasury, and customer data management. Provides production support, incident resolution, root-cause analysis, and stakeholder collaboration across business, risk, finance, compliance, and technology teams.

Analyze product, engineering, delivery, and commercial data to define KPIs, identify trends, and support evidence-based decisions. Build Power BI dashboards from product telemetry to measure adoption, engagement, feature usage, and customer behavior. Improve data quality, automate recurring reporting, and communicate actionable insights to technical and non-technical stakeholders.

Build and maintain large-scale geospatial datasets and ETL pipelines for production use. Perform GIS visualization, spatial analysis, data extraction, transformation, validation, and quality assurance using QGIS or ArcGIS, Python, PySpark, SQL, AWS, and geospatial databases. Automate workflows, document methodologies, support internal GIS requests, and collaborate with analytics and business teams to deliver accurate location-based data.

Monitor and improve risk data quality by validating processing, reviewing day-over-day anomalies, investigating exceptions, and coordinating remediation with upstream teams and data consumers. Maintain validation lineage, refine rules, support data governance, and communicate data availability. Partner with finance, risk, technology, and business teams to define requirements, test changes, and improve data processes and user experiences.

Leads data quality and governance activities across business domains, serving as a subject matter expert and liaison for data stakeholders. Responsibilities include quality monitoring, automated reporting, issue investigation, root-cause analysis, data validation across legacy and cloud systems, governance implementation, documentation, and continuous process improvement. The role supports data initiatives, drives business adoption, manages controls and attestations, and communicates data quality findings and recommendations to stakeholders and executives.

Develop and maintain Tableau dashboards, visualizations, reports, and BI solutions. Gather requirements from clients and stakeholders, define KPIs and metrics, analyze business processes, and translate business needs into analytical solutions. Perform SQL-based analysis, dashboard quality checks, validation, documentation, and data governance. Collaborate with Data Engineering teams, present insights through storyboarding, document meetings, and track work using JIRA.

Leads analytics for a mobile gaming business, owning investigations into funnels, retention, churn, player value, monetization, game economy, and experimentation. Builds churn prediction and forecasting models, designs and analyzes A/B tests, architects data pipelines, ensures data quality, creates self-service dashboards, communicates recommendations to leadership, and mentors analysts. Requires strong SQL, Python, statistical reasoning, visualization, and experience working with large-scale data systems.

Own the analytics function for JLL’s Lease Abstraction Enterprise Platform. Build KPI dashboards, reports, and visualizations; analyze operational data; identify trends, anomalies, and optimization opportunities; establish measurement standards; present insights to stakeholders; lead data-driven improvement initiatives; document methodologies; train users; and ensure data accuracy and integrity.

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.

Build scalable data solutions, semantic models, data marts, transformation pipelines, dashboards, and analytics solutions using Microsoft Fabric, Snowflake, dbt, Power BI, and Tableau. Analyze business, financial, and operational requirements, deliver data-driven insights, support AI-enabled analytics, and collaborate with stakeholders across the organization.