Top Data Analyst Jobs

The Senior Analyst will support Data Governance policies, document procedures, collaborate with stakeholders, and assist in training and audits.

The Senior Analyst will support data risk assessments, translate data governance standards into practical tools, and enhance integration of data controls in critical business processes.

Drive technology risk reporting and analytics for ERM: analyze risk datasets, build Power BI dashboards, integrate IT/IS/third-party data, assess controls using industry frameworks (COBIT, NIST, ITIL, DCAM, DMBOK), support RCSA, and advise business units on risk mitigation and control improvement.

Support implementation and post-implementation ERP reporting and analytics: gather/report requirements, configure and test reports, write specs and user procedures, create/retrofit reports, execute testing, document issues and enhancements, train users, and provide ongoing maintenance and optimization.

The ERP Data Analytics and Reporting Analyst handles requirements gathering, report configuration, and post-implementation support for the ERP system.

The Analyst will manage data and perform financial analysis on private equity and alternative assets, while providing feedback for the analytics platform.

Design and maintain Power BI semantic models and Microsoft Fabric analytics solutions. Build scalable star schemas, DAX measures, Spark/PySpark pipelines, AI-enabled data experiences, and operational dashboards while partnering with engineers and BI teams to improve data quality, performance, and governance.

Own and QA high-impact retail data products: design and run QA, investigate and resolve complex data quality issues, collaborate with Insights and Engineering, improve automation and product reliability, and communicate methodology and limitations to clients.

Support VHA specialty care programs with enterprise data management, BI, reporting, and automation. Build Power BI dashboards, automate data acquisition with Microsoft Power Platform, integrate solutions with VA systems, analyze healthcare/financial data, and produce executive reporting, documentation, and training to support decision-making and performance improvement.

Analyze C&DS project data to produce actionable insights. Build data pipelines, reports, visualizations and predictive/prescriptive models. Collaborate with IT, data governance, and business stakeholders to enable data-driven decision-making, support reporting needs, and ensure data quality and access.

Lead master data governance for product/material domains across Agile PLM and SAP S/4HANA/SAP MDG. Define governance, document requirements and processes, support MDG design and integrations, drive data migration/cleansing, perform impact analysis, and champion data quality across supply chain, manufacturing, and IT stakeholders.

The Data Quality Analyst will validate data accuracy, develop automated testing frameworks, analyze discrepancies, and collaborate on data governance with stakeholders.

Serve as product-owner/business analyst for actuarial data and tools within the Global Data Office. Translate actuarial requirements into data engineering specs, lead Agile ceremonies, manage product backlog and roadmaps, align stakeholders, and ensure data governance, lineage, testing, and quality for actuarial reporting, reserving, and pricing use cases.

The Data Quality Analyst audits and standardizes data from various internal sources to ensure accuracy. Responsibilities include developing reports, building data pipelines, and collaborating with teams to manage data integrity.

Lead data governance activities including profiling, metadata population, data quality remediation, and standards enforcement. Work cross-functionally to implement Informatica-based cataloging and protection, automate data protection, deliver training, and recommend improvements to data quality, standardization, and transformation.

Own end-to-end analysis of payments, chargebacks, and user lifecycle to identify drivers of net loss. Deep-dive into fraud cases, design and evaluate A/B experiments and risk-rule changes, build monitoring dashboards, partner with Risk, Payments, and Product to convert insights into mitigations, and run ad-hoc analyses of emerging loss trends.

Lead end-to-end analytics work: define core metrics, build reliable data models and pipelines, deliver dashboards and insights, and partner cross-functionally to drive product and business decisions. Mentor stakeholders, document data, and help scale analytics capabilities on an event-driven platform.

Maintain data quality and build automated reports using Microsoft SQL tools, SSRS, and SSIS. Support client implementations, test data exchanges, streamline processes, and produce clear technical/user documentation while responding to internal and client requests.

Responsible for troubleshooting escalated data issues, resolving data discrepancies, monitoring ETL jobs, performing data engineering and development work (20-25% time), automating operational tasks, building tabular models and reports, and documenting knowledge for Tier 1/2 support. Must support production issues outside normal hours.

Troubleshoot escalated data issues, resolve data discrepancies, monitor ETL jobs, perform data engineering and development tasks (20-25% effort), build tabular models and reports, document knowledge base, and support production issues including off-hours.

Manage and sustain enterprise master data across Infor LN and integrated systems. Perform data analysis, enforce governance standards, build dashboards and automation using AI-enabled tools, standardize intake workflows, support system implementations, and partner cross-functionally to improve data quality and synchronization.

Partner with business and engineering teams to define and deliver enterprise data products (dashboards, KPIs, semantic layers). Translate stakeholder needs into requirements, manage scrum priorities, design analytics prototypes, perform reporting and KPI monitoring, ensure data quality and governance, and drive adoption via user research, documentation, and change management.

Lead analytics strategy for federal programs: perform statistical modeling, forecasting, and data mining; build dashboards and automated workflows; ensure NIST/FISMA compliance and data quality; present findings to government stakeholders; mentor junior analysts and manage analytics workstreams.

Collects, organizes, and validates telecommunications and technical data from multiple sources, inputs and reconciles records to meet quality standards, analyzes databases for consistency and patterns, performs data extraction and basic automation, generates reports, and mentors junior staff while adhering to security and ISO 9001:2015 procedures.

Designs, implements, and maintains master data management solutions; analyzes, cleanses, and enriches data; ensures data governance and integrity; troubleshoots MDM issues and provides recommendations to the Government.