Top Data Analyst Jobs

The Sr. Data Analyst will perform data analysis for a pharmacy project, handle data issues, support data management processes, and assist in ETL development. Strong experience in SQL and healthcare is required.

The Product Operations Analyst analyzes product data and customer behavior to inform strategy, supports performance tracking, and drives continuous improvement through data insights and experimentation.

Lead design and development of dashboards and reporting (Tableau) integrating multiple data sources. Perform advanced SQL extraction, Excel analysis, and visualization; translate business requirements into actionable insights. Ensure data accuracy, mentor junior analysts, and collaborate with technical teams. Position is on-site in Melbourne, FL and requires an adjudicated U.S. Secret clearance.

Support practice groups and leadership by collecting, cleaning, integrating, and analyzing data from finance, timekeeping, and billing systems. Build SharePoint lists, automated forms, and dashboards in Power BI; use SQL, Python, PowerShell, and APIs for data integration and automation. Produce recurring and ad hoc staffing, utilization, and productivity reports and coordinate with People Ops, Finance, Recruiting, and practice leaders to optimize staffing and workflows.

Support practice groups and firm leadership by collecting, cleaning, integrating, and analyzing data from finance, timekeeping, and billing systems. Build reports, Power BI dashboards, SharePoint lists and automated workflows using SQL, Python, PowerShell, Power Automate, and APIs. Track staffing, utilization, capacity, and productivity; coordinate staffing with People Ops, Finance, and Practice Group leaders. Improve data quality, system integrations, and operational processes to inform resource planning and decision-making.

Serve as primary Snowflake administrator and data pipeline engineer: manage Snowflake security, performance, multi-account administration; design and maintain ingestion pipelines and curated data layers; enable AI agents and semantic views; activate/test Snowflake previews; document runbooks and train teams.

Design and enhance a global corporate hierarchy framework by defining entity relationships, building parent-subsidiary linkages, enforcing governance rules, and performing data analysis to improve linkage quality and integrity. Collaborate with business, product, and engineering teams to deliver scalable solutions, support project delivery, and communicate with stakeholders and executives.

Perform data quality checks, develop analyses and financial models, implement test plans, audit data integrity, prepare reports and present insights to stakeholders. Support small-to-medium client projects and product implementations, and collaborate across business units to manage parts of project/product lifecycles.

Design, build, and maintain production-grade ETL/ELT pipelines and data models using dbt, Spark, and cloud platforms. Manage ingestion, data quality, observability, semantic layers, and BI outputs. Collaborate with analysts and data scientists to deliver governed, high-quality data products and implement DataOps and CI/CD practices.

Lead product-focused data initiatives by translating stakeholder needs into buildable data features. Partner with engineering, QA, and operations to define functional requirements, acceptance criteria, and test cases. Write and use SQL for analysis, perform functional testing and sign-off, track usage trends, and iterate on data products, pipelines, automation, and AI-driven solutions to support product growth.

Lead data operations reporting and deep-dive analysis to improve data quality, customer experience, and operational health. Aggregate data from multiple sources, present actionable recommendations to leadership, partner with stakeholders on solutions and enterprise initiatives, and mentor junior team members.

Support and maintain consumer data platforms by building reusable data models, CI/CD and testing for data workflows, translating stakeholder needs into analytics layers, preparing and monitoring ML features, and ensuring data quality and governance to enable marketing, retention, and personalization efforts.

Maintain and build a Metadata Application Profile (MAP) to integrate metadata from multiple data stores into a search and discovery system. Assess metadata quality, run queries using UI/API/Postgres/Elasticsearch, create design documents for new data stores, coordinate with data stewards, and investigate metadata discrepancies and tickets to enable enterprise-wide imagery and data discovery.

Lead enterprise data governance and analytics across multiple master data domains. Perform complex data research, design analytical models, maintain metadata and data catalog, manage access and audits, advise stakeholders, standardize critical data elements, and lead cross-functional projects to improve data quality, consistency, and usability.

Lead data governance and analytics across multiple master data domains (Customer, Vendor, Finance, Marketing, HR, Supply Chain). Perform complex data analysis, design data-mining models, develop scalable reporting, manage access controls and audits, maintain metadata and enterprise data catalog, consult stakeholders to standardize critical data elements, and lead cross-functional projects to improve data quality and governance.

Lead enterprise data governance strategy and data risk/control frameworks. Partner with business lines to implement policies, monitor controls, track issues, produce metrics and recommendations, and support regulatory/audit responses. Drive adoption, performance measurement, and stakeholder communications across global functions.

Lead institutional analytics and data management for teaching and learning initiatives: manage and analyse survey data (GES, module and student surveys), develop dashboards and reports, ensure data quality and systems operation, create insights on academic quality and graduate outcomes, and drive analytics automation and improvements.

Lead and manage client data contribution, quality, and remediation projects. Coordinate discovery, technical requirements, testing, validation, and production implementations. Monitor and analyze client data, perform root-cause analysis, audit data, provide remediation guidance, and collaborate with internal teams and clients to ensure data quality and ongoing operations.

The Growth & Development Analyst role involves deal origination, market research, financial analysis, and execution in data center development, focusing on financial modeling and strategic insights.

The Growth & Development Analyst role involves evaluating data center development opportunities, conducting market research, performing financial analysis, and managing transactions while supporting senior leaders in high-impact projects.

Design and build interactive dashboards and UIs using tools like Qlik Sense, Tableau, or Power BI. Clean, wrangle, and analyze data from warehouses and big-data sources. Define reporting objects, metrics, filters, and visual best practices to deliver actionable insights for DoD clients. Work requires Secret clearance and a bachelor’s degree.

Validate and triage clinical data across HL7, FHIR, and Databricks pipelines using SQL. Trace transformations end-to-end, identify and remediate data quality issues, partner with engineering/product/clinical teams, document findings, and support client go-lives to ensure clinically accurate, production-ready data.

Validate and troubleshoot clinical data pipelines for PhareOS across HL7, FHIR, and standardized Databricks/dbt layers. Execute complex SQL validations, trace HL7-to-FHIR transformations end-to-end, investigate and remediate data quality issues, build Databricks queries/notebooks, and collaborate with engineering, product, clinical, and vendor teams to ensure production-ready client data and successful go-lives.

Maintain and ensure accuracy of legislative and political data; build ingestion pipelines and scrapers; use SQL and LLM tools to query and report; perform day-to-day data quality control, investigate and resolve data issues, research new data sources, and translate findings into actionable insights for cross-functional teams.

Support enterprise data governance and privacy by processing data-use requests, assessing privacy requirements, and collaborating with legal, security, risk, and IT stakeholders. Use analytics and database tools to extract and analyze data, support GDPR/CCPA compliance and audits, define privacy safeguards, and improve governance processes while managing multiple workstreams and maintaining clear documentation.