Top Data Analyst Jobs

The Junior Data Analyst will support reporting, analytics, and data quality, collaborate with stakeholders, and develop reports and dashboards.

Maintain and analyze HR system data, design and program reports, ensure data integrity and security, support people analytics and ad hoc reporting, collaborate with HR and IT, and assist in system recovery and automation.

The Junior Data Analyst will conduct qualitative and quantitative analysis, evaluate processes, and provide scheduling and documentation support for a DHS client.

Transform complex data into actionable insights, develop reports and dashboards, ensure data quality, and manage client relationships to meet their data needs.

Support settlement programs by answering client data questions, validating claimant data and calculations using SQL/Python, performing quality checks, documenting solutions, and collaborating with litigation, engineering, and product teams.

The Senior Data Analyst will identify finance user needs, deliver technology solutions, manage projects, and train users, providing strategic insights from complex data sets.

Analyze complex datasets to support investment analyses, validate growth initiatives, and develop data-driven narratives for clients. Responsibilities include data visualization, financial modeling, and collaboration with investment bankers.

Lead metadata and data catalog operations: curate metadata, document lineage, maintain business glossary, develop governance procedures, enable stewards, support catalog onboarding, and produce metrics to improve metadata quality and adoption across enterprise data domains.

Own and define operational metrics in BigQuery; validate and monitor data quality; build dashboards, lineage, and tooling; partner with engineering, product, and operations to turn analyses into repeatable KPIs and process improvements.

The Senior Data Analyst will provide analytical support for military assistance programs, ensuring data integrity, visualizations, and trends analysis while collaborating closely with clients.

The Senior Data Analyst will lead data analytics projects, train team members, and research new technologies to enhance data-driven insights for clients.

Support development and delivery of reporting and BI solutions: acquire, transform, validate, and present data; build automated ETL workflows, dashboards, and reports; ensure data quality and governance; translate business requirements into actionable reporting; collaborate with Data Engineering and Visualization leads; support testing, deployment, and stakeholder training.

Lead validation and quality assurance for healthcare claims, eligibility, provider, member, and reference data. Perform profiling, reconciliation, ETL validation, anomaly detection, root cause analysis, and develop complex SQL queries. Define data quality metrics, support tooling and automation, mentor analysts, coordinate offshore teams, and ensure HIPAA and regulatory compliance to improve analytics accuracy and client outcomes.

As a Senior Data Analyst, you will analyze game telemetry data, translate business needs into insights, and guide technical teams. You will also lead exploratory data analysis and maintain data quality practices.

Design, define, and implement data quality management for Customer MDM. Analyze and integrate MDM processes with Sales, Marketing, Support, and Finance systems. Perform data cleansing, standardization, matching/merging, reporting, and statistics using SQL and Excel.

Design, build, tune and maintain enterprise data structures and databases. Gather and document business and technical requirements, perform data profiling, mapping and validation, support ETL and data warehouse implementations, coordinate testing and production rollout, provide ad-hoc datasets and reporting, and participate in data governance and control reporting.

Support Americas Sales and Marketing by performing CRM administrative and audit tasks, executing SAP web-interface tasks, running reports, performing Excel-based analysis and data audits, managing support inboxes, documenting processes, and training/transitioning work to third-party providers.

Lead sales operations analytics for Grocery and Retail: design dashboards and models, analyze sales and market trends, support forecasting and capacity planning, optimize sales funnel performance, deliver strategic insights to sales leadership, and collaborate with data engineering/BI using SQL, Python, and visualization tools.

Analyze large datasets using complex SQL and advanced Python (Pandas, NumPy); build and optimize data pipelines, automate tasks, and create Google Sheets reports and dashboards. Collaborate cross-functionally, present insights to technical and non-technical stakeholders, and support data-driven decision making.

Lead design and buildout of an Operations Intelligence Warehouse (BigQuery, dbt, Metabase), define metrics and data quality standards, create dashboards for throughput and cycle time, join ops to GTM/financial data, run variance/root-cause analyses, and partner with Data Engineering and stakeholders to turn operational telemetry into actionable insights.

Support data analysis and reporting for pricing, underwriting, claims, and product performance. Prepare and validate reports, create visualizations, document data sources, and assist stakeholders with analyses and presentations.

Support practice group leadership by collecting, cleaning, integrating, and analyzing data across finance, timekeeping, and billing systems. Build reports, dashboards, and automated workflows (SharePoint, Power BI, Power Automate) to monitor utilization, staffing, and productivity. Coordinate staffing, prepare recurring and ad-hoc analyses, and translate data into actionable recommendations for practice and firm leadership.

Support practice groups and firm leadership by collecting, cleaning, integrating, and analyzing data from finance, timekeeping, and billing systems. Build reports, dashboards, and automated workflows (SharePoint, Power BI, Power Automate). Track staffing, utilization, and productivity; identify capacity gaps; coordinate staffing with People Ops, Finance, and Practice Group leaders. Assist system integrations, data QA, and ad hoc analysis to improve operational efficiency and decision-making.

Perform data analysis and programming on large Medicaid claims datasets using Python, SQL, and SAS; produce client deliverables (reports, proposals, presentations); collaborate with programmers, actuaries, and clinicians; support AI-enabled tools and work on team-based consulting projects to improve Medicaid program outcomes.

Lead development of complex data models, datasets, and Tableau dashboards; perform deep analyses of large datasets; present insights to senior leadership; optimize SQL queries and Snowflake-based pipelines; mentor junior BI team members and partner with business units to define KPIs and drive data-driven decisions.