Top Data Analyst Jobs

Develop, maintain, and investigate recurring and interactive reports and dashboards (primarily Power BI) using internal and vended data sets. Consult with Planview and IT partners on data structure and transmission, meet reporting deadlines, present findings, and follow department best practices to support IT Project Management Office objectives.

Lead FHIR implementation: map healthcare domains to FHIR resources, build mappings/extensions/value sets, collaborate on API design, validate conformance, ensure data quality, and support testing and documentation across development and UAT.

Support randomized control trials and A/B tests for Party at the Polls: maintain experimental data tables, prepare samples, analyze results (pre/post-election), prioritize sites, and produce reports and timely program performance analysis.

The Data Analyst Supervisor leads a team to provide data-driven insights, oversees projects, ensures data accuracy, and collaborates across departments for strategic decision-making.

Analyze A/B experiments and large datasets to determine why experiments performed well or poorly. Communicate results to business partners, validate and improve data-driven decision processes, build key metrics and modeling reports, and collaborate with business and engineering stakeholders.

Develop, test, and maintain analytics and reports for pharmacy operations. Translate designs into code, validate reports, document business rules and logic, and support ad-hoc and workplan analytics using SQL and Tableau.

Perform end-to-end data analysis to support business strategy and operations. Responsibilities include data mining, aggregation, trending, inventory and program analysis, platform performance/milestone analytics, data governance, testing controls, monitoring data quality, and recommending policy and standards to improve operational performance.

Contract Data Analyst to perform data mapping and database-related work. Requires minimum 3 years database development experience, strong XML skills, ability to learn complex multi-state legacy systems, excellent communication, organization, and attention to detail. Must work independently and clear a background check.

Participate in implementing a new state education data repository: analyze source data, create source-to-target mappings, and develop views and stored procedures. Assist application teams by designing databases from business requirements using enterprise data modeling best practices.

Perform data mining, cleaning, transformation, validation, and analysis. Build and run T‑SQL/MS Access/DB2 queries, create standard and ad-hoc reports (SSRS, Tableau), develop test plans, schedule and deliver reports, identify trends and resolve data issues, and communicate results to stakeholders.

Onsite senior data analyst supporting data architecture and ETL. Design data mappings, perform data modeling, ensure data quality, document database entities, and support SQL Server repositories and application development teams.

Onsite Business Intelligence Developer supporting stakeholders to gather BI requirements, identify data sources, design BI processes, build reports, analyze processes and requirements, perform testing, manage project phases, and deliver data reporting using Tableau, SSRS and T-SQL.

Analyze and report on data center operational metrics (electrical usage, PUE, incidents, tickets, headcount), maintain internal/external data repositories, manage external reporting partners, build cost and forecasting models, prepare executive presentations, and support budgeting and performance tracking across a global data center portfolio.

The BI Data Analyst develops database solutions, creates reports, analyzes data systems, and maintains database processes while collaborating with data architects.

The role involves transforming data into insights, conducting analysis, building data models, and collaborating with marketing teams to optimize campaigns. Strong skills in SQL, Python, and data visualizations are essential.

The role involves managing investment data, performing analytics, supporting fundraising and marketing efforts, and ensuring data quality and governance.

The Data Analyst supports the IT team by interpreting complex data, developing databases, conducting analyses, and creating visualizations for data-driven decision making.

The Data Analyst II conducts data analysis, prepares reports and visualizations, partners with stakeholders, and mitigates data quality issues.

The Data Analyst III conducts empirical research in health economics and policy, performing data analysis, literature reviews, and contributing to study design, with a focus on academic research collaboration.

Lead audit data analytics for assigned areas, improve audit effectiveness, collaborate with teams, and execute data strategies and analytics solutions.

Support large-scale voter contact programs by building and maintaining clean data tables, creating audiences and A/B test groups, prioritizing sites, delivering timely analysis and reports, and automating dashboards and processes to surface real-time insights for program teams.

Provide supply chain data analysis, build/maintain data pipelines and validation checks, develop dashboards and executive metrics (Power BI/Tableau), support OSCQ analytics and SAFe Agile teams, and drive operational improvements through data-driven insights.

Analyze customer implementation and product usage to identify drivers of adoption, retention, and expansion. Build dashboards, quantify configuration and workflow impacts, surface deployment friction, and partner with Product, Sales, and Customer Success to create evidence-based playbooks and metrics that inform roadmap and go-to-market strategies.

Analyze datasets to generate reports and visualizations that inform business decisions. Produce regular reporting, create data visualizations, and work cross-functionally to support data-driven strategies with attention to accuracy.

Design and deliver reusable supply-chain analytics products and persona-based dashboards using the modern data stack. Partner with operations and customers to prioritize requests, leverage AI to accelerate analysis, and tie insights to measurable business outcomes. Support data maturity, integration, and agile product delivery.