Top Data Analyst Jobs

Prepare financial reports, support master data management and integrity, conduct market research analysis, and participate in improving master data processes. Requires strong analytical, communication, organizational, and computer skills; willingness to relocate to the US and commit to at least one year as a consultant.

Use client platform data to identify trends and actionable insights. Create reports, dashboards, and metrics; perform statistical and predictive analysis; validate data quality; integrate data sources; collaborate with stakeholders and technical teams to optimize systems; evaluate tools and train users on analytics capabilities.

Support design and delivery of a predictive lifecycle management solution in Palantir Foundry. Perform exploratory data analysis, feature engineering, data quality assessment, and source analysis. Build data dictionaries and ERDs in Figma, document technical solutions, communicate insights to stakeholders, and participate in customer meetings.

Build and maintain data solutions for risk products: mine diverse data, develop BI dashboards and metrics, perform analyses to inform strategy, enforce data quality/lineage/governance, and collaborate with tech teams on access and security. Support self-service frameworks and monitor data quality.

Run and maintain reports and analyses using the agency MIS and external databases; manage referrals and chart reviews; track performance metrics and forecast outcomes; coordinate with EQI and IT to develop measurement tools; produce board and executive reports; perform quality assurance, staff training, and ad hoc data projects to inform program operations.

The Data Analyst analyzes complex datasets, identifies trends and risks, validates business requirements, and collaborates with technical teams to support reporting and decision-making.

Designs and maintains BI data models, reports, dashboards, and visualizations. Performs should-cost and variance analyses, tracks procurement savings, supports category managers with strategic analyses, and extracts/transforms ERP transactional data. Collaborates with IT and stakeholders to ensure data accuracy, security, and adoption of best practices.

Analyze customer sales and behavioral data to impact decisions, develop reports, optimize campaigns, and enhance user experience in ecommerce.

As a Trainee Data Analyst, assist in data collection, cleaning, analysis, and support teams with reporting needs using SQL and visualization tools.

The Digital Marketing Data Analyst will perform data analysis, attribution modeling, user journey tracking, A/B testing, and generate insights from data for marketing strategies.

The Senior Digital Data Analyst will analyze digital data, create attribution models, segment audiences, and present findings to clients, leveraging multiple datasets.

The Data Analyst will provide data analysis and business intelligence services, integrating data across various technologies and communicating with stakeholders to develop insights and solutions.

Analyze digital customer journeys and site behavior to identify friction, explain marketing performance, and provide actionable insights. Maintain dashboards, support A/B and multivariate testing, collaborate with developers on tagging and tracking, and drive optimization to improve conversion and retention.

Perform data risk analysis, support permissible purpose audits, design governance controls, map datasets to use cases, produce dashboards and documentation, and contribute to roadmaps identifying capability gaps.

As a Senior Marketing Data Analyst, you'll analyze revenue impacts from marketing, optimize growth strategies, evaluate channels, and establish scalable reporting systems using SQL and AI tools.

Design, build, and maintain interactive Power BI dashboards (including Fabric workspaces). Analyze data to identify trends, ensure data quality, collaborate with stakeholders to gather requirements, and present actionable insights to support decision-making.

The Big Data Analyst will analyze complex data, communicate findings, work with teams, and solve problems related to BI and case management.

Collect, clean, validate, and analyze large datasets across manufacturing, engineering, marketing, sales, pricing, and ERP. Build data models, reports, dashboards, and visualizations (SQL, Python, Power BI, Excel). Provide actionable insights to stakeholders, support data governance, track initiative success, and collaborate cross-functionally to improve operations.

Query and extract data from multiple vendor programs, maintain datasets in Oracle/SQL, build and distribute departmental reports, implement ETL/automation with exception handling, reconcile data loads into relational and dimensional databases, and perform assigned research and analysis.

Advance investment data, reporting, and technology capabilities by designing scalable data pipelines, monitoring and resolving data exceptions, building reports and dashboards, supporting product management and UAT, improving automation and governance, and partnering cross-functionally to maintain data quality and documentation.

Lead global marketing data, analytics, and reporting strategy. Drive data quality, unification, and acquisition; build measurement plans, predictive models, and PowerBI reporting; partner with executives to create a data and reporting roadmap, enablement workflows, and analytics governance to improve marketing effectiveness.

Lead the requirements and data-mapping work for an AWS-based data platform: elicit/document business and data requirements, build source-to-target mappings and data dictionaries, define testable data quality rules, support dimensional modeling and UAT, coordinate across engineering/risk/platform teams, manage BA backlog in ADO/Confluence, and leverage AI assistants to accelerate analysis and test-case generation.

Audit and reconcile marketing and lead data end-to-end, maintain campaign tracking and platform integrations, troubleshoot data flow issues, manipulate large datasets to identify discrepancies, coordinate with vendors and stakeholders, and recommend process improvements to ensure accurate marketing-to-intake reporting.

Own end-to-end analytics for the Pro product: build production data pipelines and dbt models, define north-star metrics, design dashboards and full-funnel reporting, lead A/B experimentation and causal inference, embed AI tooling, and deliver clear data-driven recommendations to product and leadership.

Maintain and assure the quality of automotive catalog data: load, review and validate parts, vehicle, labour and interchange information; extract and transform ACES/PIES/XML feeds; resolve data-quality issues; use Excel, SQL and catalog configuration systems; partner with product, development and customer teams to ensure accurate, timely catalog content.