Top Data Analyst Jobs in Hyderabad

Analyze healthcare claims, provider, financial, and operational data to identify trends, anomalies, and inefficiencies. Build automated reports, dashboards, and forecasts using SQL, Python, and BI tools to support audit, finance, and operations, ensuring data quality, SLA monitoring, and actionable recommendations.

The role involves managing a team of data analysts to ensure the quality and usability of healthcare market datasets, implementing analytical standards, and translating complex data outputs into actionable business insights.

Design, develop, operate, and optimize cloud-native ETL pipelines using Azure, Databricks, Spark, Python, and SQL. Modernize on-premises workloads to cloud architectures, implement data validation and monitoring, and ensure scalable, reliable, governed data solutions. Collaborate with cross-functional teams on complex data requirements, contribute to data warehouse implementations, tune performance, and document engineering processes and systems.

Designs data structures, schemas, queries, and engineering solutions for healthcare and reporting systems. Analyzes requirements, creates technical designs, supports QA and UAT, participates in Scrum ceremonies, performs defect analysis, and assists with project releases. Requires strong problem-solving, communication, presentation, and data engineering skills.

Gather and document business and data requirements, translate needs into user stories, perform data gap analyses and source-to-target mapping, and validate data outputs using SQL. Support data profiling, quality monitoring, data lineage, QA, Agile ceremonies, documentation, workflow improvements, change management, and stakeholder communications across client, product, engineering, and business teams.

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 and enhance a sales crediting platform supporting incentive compensation. Build scalable SQL and Python data pipelines using Databricks, implement validation and reconciliation frameworks, troubleshoot production issues, and deliver analytics and dashboards. Partner with business, IT, and data stakeholders to translate requirements into technical solutions, automate processes, manage platform enhancements, and explore AI applications for anomaly detection, data quality, and operational efficiency.

Designs scalable, secure data architectures; performs proof-of-concepts; troubleshoots technology and environment issues; develops Azure cloud applications; and migrates BDPass data pipelines to Azure. The role requires cloud platform expertise, data security and privacy knowledge, programming in Python, Java, and SQL, big data technologies, data warehousing, modeling, data management, software development, and agile methodologies.

Designs scalable, secure cloud data architectures; performs technology proofs of concept, troubleshoots across environments, and migrates BDPass data pipelines to Azure. The role requires expertise in AWS and Azure, data engineering programming, big data technologies, data warehousing, modeling, security, software development, and agile practices, along with strong problem-solving, communication, and collaboration skills.

Manage and resolve client inquiries involving banking datasets, analyze data to produce actionable insights, and support quality assurance sampling workflows. Develop Power BI dashboards and use SQL and Python for advanced data manipulation, analysis, automation, and product enhancement. Collaborate with cross-functional global teams, maintain data integrity, and adapt to varying shifts across time zones.

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.

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.

Build and manage production data workflows, data quality dashboards, validation checks, and governance processes. Analyze large datasets to identify trends and opportunities, automate manual processes, and deliver actionable recommendations. Collaborate with vendors and cross-functional stakeholders to clarify requirements, communicate workflow results, track project status, and resolve issues. Serve as a data resource while handling ad-hoc analysis requests.

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.

Design, develop, and maintain interactive Power BI/Fabric dashboards, conduct data analysis to surface trends and insights, collaborate with stakeholders to gather requirements, ensure data quality through ETL and modeling, and present findings to inform business decisions.

Perform gap analyses across trading data from multiple source systems, identify discrepancies, build automated reports using Python and SQL, create visualizations (Power BI or Python libraries), present findings to stakeholders, and coordinate with upstream/downstream teams to implement logic and document requirements.

Execute SOPs, checklists, and QA to meet SLAs. Prepare and validate data for model development, identify and resolve discrepancies, support reporting, and communicate risks. Maintain HIPAA/PHI compliance and ISMS alignment while working shifts in a fast-paced operational environment.

Assist in designing, developing, and maintaining data product pipelines. Collate and analyze data using SQL, Python and GCP. Support and coach colleagues, follow established procedures, identify process improvements, and perform prescribed project and product engineering activities under senior guidance.

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

Design, develop, and maintain scalable ETL pipelines and data integrations. Build and optimize complex SQL, Python automation, and reporting solutions (Power BI/Tableau/SSRS). Troubleshoot performance, ensure data quality and governance, participate in client-facing discussions, code reviews, deployments, and technical design.

Design, build, and maintain data extraction and transformation pipelines using Azure Data Factory and Databricks. Develop complex SQL (joins, CTEs) and PySpark code, ensure data quality and business logic, troubleshoot production issues, manage CI/CD via Azure DevOps, integrate with Veeva/Salesforce, meet SLAs, document processes, and support EST shift hours while collaborating with technical and business stakeholders.

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.

Manage pharmaceutical commercial data quality, availability, completeness, governance, and processing across global stakeholders. Maintain requirements, business rules, metadata, reports, SOPs, and compliance controls; investigate data issues and support sales, claims, MDM, and omnichannel inquiries. Develop analytics, reporting, automation, data catalogs, profiling, and quality frameworks using tools such as SQL, Python, Power BI, Informatica, and AWS. Collaborate with digital teams, vendors, and US data management stakeholders to improve processes and support commercial operations.