Top Data Analyst Jobs in Hyderabad

Designs, standardizes, migrates, transforms, validates and optimizes data across multi-database platforms. Builds and maintains ETL pipelines, supports client data lifecycles, troubleshoots production defects, contributes across SDLC, and maintains code in GitHub. Supports off-hours processing and ensures data quality and policy adherence.

Lead the data solutions strategy for PR&C PSP division, managing data initiatives, teams, and collaborating on analytics projects. Ensure compliance, governance, and optimize data services while communicating technical solutions to stakeholders.

The Software Engineer - Data Analyst / Developer will support the BI team by analyzing business needs, developing reports, dashboards in Tableau, ensuring data quality, and providing user support.

Analyze complex supply chain data to improve performance, monitor inventory, develop reports, and support key initiatives in collaboration with stakeholders.

Drive data quality and AI readiness for Skills and Job Architecture: investigate root causes, build Python/SQL data profiling and remediation pipelines, implement automated monitoring (Power BI), partner with Workday and governance teams, and ensure HR skills data meets AI-ready standards.

The role involves collecting, preparing, and reporting statistical data, ensuring data accuracy, and providing technical support for analytical tools. Communication with stakeholders and maintaining data dictionaries are key responsibilities.

Lead logistics analytics projects: design KPIs, dashboards, and reports (Power BI/Excel); perform root-cause analysis; support implementations, integrations, and cross-functional decision-making.

Lead metadata and data governance for corporate functions: maintain the enterprise data catalog, manage metadata accuracy, support data lineage, data quality, and critical data element governance, onboard source systems with Data Capability, provide training and documentation, serve as Informatica metadata subject matter expert, handle escalations, and support GIDS leadership in governance initiatives.

Lead end-to-end marketing analytics: design and maintain data models and ETL, ensure data quality in cloud warehouses, build automated Tableau dashboards, perform deep SQL-driven campaign and funnel analyses, support A/B testing, and translate insights into strategic recommendations for marketing stakeholders.

Design, build, and maintain cross-vendor market data pipelines and QA processes. Investigate complex data issues, handle escalations, collaborate with product and engineering via JIRA, and ensure data accuracy for equities fundamentals, estimates, and market data.

The role involves maintaining and improving Power BI dashboards, troubleshooting data models, ensuring data accuracy, and preparing data using Python. Communication in English and Spanish is essential for stakeholder interactions.

Lead end-to-end analytical projects: analyze complex datasets, build scalable SQL and Python (Pandas) solutions, create dashboards and reporting frameworks, perform root-cause analysis, gather business requirements, present insights to senior stakeholders, and mentor junior analysts to establish best practices.

The Senior Analyst will own Pricing Tools, manage data governance, drive pricing strategy decisions, execute audits, and enhance operational effectiveness.

Design, develop, and support analytics solutions, dashboards, reports, and data models. Prepare and transform data, ensure data quality and governance, collaborate with stakeholders, leverage AI to accelerate delivery, and drive process improvements to enable data-driven decisions.

Design and implement enterprise-scale data pipelines and governed Power BI datasets; build analytics dashboards using Microsoft Fabric and Snowflake; integrate AI tools (Copilot Agents/Claude) for insights; enforce data governance, quality, and performance optimization; collaborate with finance and cross-functional stakeholders.

Design, develop, and support analytics solutions including dashboards, reports, and data models. Clean and transform data, ensure data quality and governance, partner with stakeholders to gather requirements, apply AI prompting/tools to accelerate delivery, and implement process and change improvements for scalable, production-ready analytics.

Analyze PB-scale trading, transactional, operational and customer data; build visualizations, ML models and experiments; translate findings into actionable recommendations for trading, operations, product and executives in a fast-paced environment.

Ensure accuracy, completeness, and integrity of Salesforce customer and account data. Build automated validation and enrichment pipelines (SQL/Python), perform large-scale cleansing and deduplication (DemandTools, Data Loader), create monitoring dashboards (Power BI), enforce governance, and apply AI/LLMs to improve matching, classification, and anomaly detection so data never blocks Quote-to-Cash processes.

Define, capture, and govern data specifications and business metadata for Platinum enterprise data sources. Document source tables, lineage, transformations, and ownership. Register and maintain metadata in governance tools (Collibra), enable certification and stewardship workflows, collaborate with engineering and analytics to ensure observable, trusted, and discoverable data products.

Lead development and implementation of data analytics strategies, build advanced models and dashboards, ensure data governance and quality, mentor junior analysts, collaborate with stakeholders and data engineering, and present insights to support strategic decision-making.

Lead the Data Desk: triage and route L1/L2 requests, perform code reviews for junior analysts, drive automation and self-service dashboards, run daily operations and people development, and ensure data quality and SLA adherence.

Manage requests for new ServiceNow reports and dashboards, resolve dashboard/reporting incidents, train users on dashboards, build executive KPIs and scorecards, engage stakeholders to gather requirements, and apply AI/Generative AI for reporting automation and insights.

Ensure accuracy, completeness, and consistency of product data by validating, cleansing, enriching, profiling, and monitoring quality. Maintain data dictionaries, lineage, metadata, governance policies, dashboards, and compliance. Collaborate with stakeholders, operations, and other data stewards; train users and gather feedback to improve data products.

Ensure accuracy, completeness, and consistency of product data by validating, cleansing, profiling, and enriching content. Define data quality standards, maintain data dictionaries and lineage, implement governance policies, build quality dashboards, collaborate with stakeholders and operations, train users, and ensure compliance with privacy and regulatory requirements.

Lead data analysis workstreams using large datasets and AWS analytics tools to define metrics, test hypotheses, perform root-cause analysis, produce insights and visualizations, and present actionable recommendations to stakeholders.