Top Data Analyst Jobs in Hyderabad

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.

Analyze business requirements, extract and investigate data, handle ad-hoc analytics requests, develop Qlik Sense dashboards, and present actionable insights. The role also improves platform stability, streamlines processes, supports business initiatives, and contributes to data science strategy. Candidates must collaborate effectively, solve problems proactively, and modify code as needed. Required technical skills include Python, PySpark, SQL, Qlik tools, and knowledge of S3 data architecture.

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, 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.

Designs, develops, administers, and supports WebFOCUS, Power BI, SQL-based reporting, and secure report-delivery platforms. Responsibilities include platform administration, report scheduling, SFTP automation, incident resolution, root-cause analysis, GDPR data purges, SQL data extraction, data-quality assessments, governance support, compliance, documentation, and stakeholder consultation.

Leads advanced data analysis, dashboard and data model development, data quality initiatives, and analytics projects. Partners with stakeholders to define business questions, validate experiments, communicate insights, and support data product lifecycles. Mentors junior analysts and applies quantitative analysis, data mining, governance, and emerging AI-enabled analytics to improve decision-making.

Supports data engineering projects involving data processing, integration, pipeline development and maintenance, data quality, analysis, and reporting. Collaborates with team members to meet data requirements, follows engineering standards, uses relevant tools and techniques, and develops expertise through continuous learning and mentorship.

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 marketing measurement and analytics: design and evaluate A/B, holdout and geo tests; analyze campaign and channel performance; build causal insights and executive-ready recommendations; collaborate cross-functionally to improve measurement frameworks and reporting.

Analyze Order-to-Cash data across ERP and business systems, developing dashboards, KPIs, reports, and automated analytics. Identify process bottlenecks, data-quality issues, anomalies, and improvement opportunities through SQL analysis, reconciliation, and root-cause investigation. Collaborate with Finance, Sales, Supply Chain, Operations, and IT stakeholders to define requirements, improve reporting, support ERP initiatives, and provide data-driven recommendations for O2C performance.

Ensures sales deal data accuracy, completeness, and integrity through profiling, validation, cleansing, standardization, reconciliation, and root cause analysis. Reviews sales classifications, renewal data, contract values, dates, and deal attributes. Documents quality rules and collaborates with Sales, Finance, IT, and other stakeholders to resolve issues and improve data governance. The role also supports automation and reporting using Excel, SQL, Power Query, dashboards, and CRM data.

Lead design and delivery of analytical products, source-of-truth datasets, semantic layers, and metric frameworks. Define and validate metrics, dimensions, data quality checks, and reporting standards. Build and maintain SQL and Python workflows, dashboards, and self-service analytics. Partner cross-functionally to resolve reporting issues, perform ad hoc analysis, ensure data governance, and mentor team members on analytics and metric governance.

Early-career Data Analyst who designs and owns core analytics, dashboards, and data pipelines. Analyze transaction, customer, and credit data to inform credit, fraud, AML, portfolio performance, unit economics, and growth. Build automations and workflows with SQL and Python, partner with cross-functional teams, and own compliance reporting and durable analytical systems.

Analyze large customer, prospect, audience, and campaign datasets using Python and SQL. Own audience selection, campaign setup, validation, execution, reporting, and data quality processes. Build automated queries, scripts, dashboards, and reusable campaign operations frameworks. Partner with marketing stakeholders to translate objectives into audience strategies, investigate data issues, optimize campaign performance, and present actionable insights.

Analyze and organize reliability data for fixed and non-fixed industrial assets, assess failure probability and consequence, develop reliability strategies, gather operations and maintenance data, facilitate customer validation, use database and office software, and support multi-site reliability projects with up to 50% travel and potential relocation.

Design, build, and govern HSW data solutions and analytics; deploy AI and automation into HSW processes; produce Power BI dashboards and regular reports; support Cority operations; drive data strategy, governance, and actionable insights to improve safety and operations.

The Senior Data Analyst will define source data, create data mapping, report inconsistencies, assist with data migration, and manage stakeholder expectations while delivering insights in financial services.

Own complex analytics initiatives from strategy through delivery, develop reports, predictive models, and analytical frameworks, and advise senior leaders with data-driven recommendations. Translate ambiguous business questions into analytical roadmaps, communicate findings to executives, mentor junior analysts, establish analytics best practices, and partner with engineering and product teams on data strategy, infrastructure, governance, telemetry, and data reliability.

Design, build, and maintain ETL/data pipelines using Sparkola, PySpark, and SQL. Validate and reconcile datasets for downstream analytics (QlikSense, Superset). Use CML for development, manage jobs via Sparkola Job Server, and liaise with business stakeholders while following governance, JIRA, and change-control processes.

Design and scale transportation analytics and tooling to optimize network performance and reduce shipping costs. Build dashboards, routing/ship-speed optimizers, chargeback/dispute systems, and cost benchmarking engines. Deliver predictive and real-time KPIs, automate processes, improve data accuracy, and provide fast ad-hoc decision support for cross-functional stakeholders.

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 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.