Top Data Analyst Jobs in Bangalore

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.

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.

Supports Finance Operations by collecting and analyzing operational data, reconciling transactions, and architecting master data solutions. The role maintains synchronized, centralized, consistent, and controlled master data across platforms, including product content management and publishing. Responsibilities involve solving lower-complexity problems, collaborating with peers, working under moderate instruction, and contributing as an individual team member. Rotational shifts may be required.

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 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.

Analyze business and product data, build data models, and maintain dashboards and reporting layers in Looker and Snowflake. Translate stakeholder questions into actionable insights, optimize SQL queries, and ensure metric consistency. Build AI-powered analytics tools and automations, support self-service data access, and communicate findings through reports and presentations. Lead analytics projects, collaborate cross-functionally, and coach junior team members.

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.

Build and own end-to-end analytics products, including data models, custom web applications, dashboards, deployment, validation, and iteration. Partner with stakeholders and engineering teams to deliver trustworthy, scalable analytics. Translate complex findings into executive narratives, apply strong visual design, explore AI-powered analytics, and develop deep business-domain expertise. This is an onsite individual contributor role requiring extensive SQL, coding, communication, and independent project ownership.

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.

Leads data infrastructure, pipeline design, automation, data quality, and analytics initiatives at scale. Builds cloud-native pipelines using SQL, Python, Spark, Databricks, and major cloud platforms; applies AI, APIs, and web scraping to automate data acquisition and enrichment. Develops dashboards, KPIs, experiments, and reporting frameworks, partners cross-functionally on strategic projects, translates technical findings into business recommendations, and mentors junior analysts.

Own operational analytics and executive reporting by transforming delivery, quality, content-source, and API data into trusted dashboards and actionable insights. Responsibilities include delivery forecasting, defect and data-quality analysis, source and integration telemetry, ROI and capacity modeling, KPI definition, and reporting cadence management. The role partners with engineering, QA, DevOps, and operations teams to improve data reliability and inform planning, resourcing, and investment decisions.

Analyzes business data, develops Power Apps, Power Automate workflows, Power BI dashboards, and data models, and translates stakeholder requirements into technical solutions. Performs data mining, root cause analysis, application support, documentation, and post-implementation improvement. Requires strong Power Platform, SQL, JavaScript, Power Fx, Dataverse, SAP, and analytics expertise, with cross-functional communication and business process knowledge. Manufacturing or inventory management experience is preferred.

Translate raw data into actionable product insights: build Tableau dashboards, maintain Snowflake/dbt data models and pipelines, write complex SQL and use Python for analysis, collaborate with stakeholders, and explore AI/ML to enhance analytics.

Own scalable data lifecycle and semantic models, enable data tooling, and deliver dashboards and product insights. Partner with Sales, TAM, Customer Success, Product, Engineering, and Program Management to define measurement strategies, document requirements, develop reusable business models, and promote privacy-conscious self-service analytics for Auth0 and enterprise stakeholders.

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.

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.

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.

Manage Supplier, Customer, and Material Master Data in SAP, including onboarding, maintenance, deactivation, data cleansing, quality remediation, governance, incident resolution, and SLA compliance. Partner with Data Stewards and global business teams across regions to resolve data issues, monitor quality KPIs, support SAP operations, document processes, and improve master data governance and operational efficiency.

Build, maintain, and optimize enterprise data platforms using Databricks, Spark, cloud technologies, and DevOps practices. Develop CI/CD pipelines, support cloud migration and automation, monitor platform health, troubleshoot incidents, and ensure reliable, secure, and scalable data services. Participate in rotational production support across global time zones, perform root cause analysis, maintain operational documentation, and collaborate with engineering, architecture, product, and business teams.

Lead the analytics function by developing dashboards, reports, data models, forecasts, and predictive models. Partner with cross-functional leaders to translate business challenges into actionable insights, ensure data accuracy, and support decisions across customer experience, sales, marketing, operations, and finance. Manage data pipelines and BI tool governance while mentoring analysts and junior data scientists, defining the analytics roadmap, and prioritizing team workloads.

Design and deliver analytics solutions by writing and optimizing complex SQL, building interactive Power BI/Tableau dashboards, performing data analysis to surface insights, working with stakeholders to translate requirements, ensuring data accuracy and performance, and automating reporting and data workflows.