Top Data Analyst Jobs

Perform high-volume data entry and document classification for investment funds, file and process emails using a filing system, analyze vendor feeds, manually price instruments, establish fund mappings, validate data quality, and support ad-hoc data requests and lookup inquiries.

Senior Data Quality Analyst responsible for source-to-target testing, SQL-based data analysis, running Informatica workflows, validating ETL results, owning QA/test issues, and collaborating with technical teams to ensure data accuracy and integrity.

Lead data quality and reporting for complaints and servicing systems: cleanse and validate data, build reports and dashboards, perform advanced statistical analyses, automate data extraction, maintain databases, and collaborate with stakeholders to surface actionable insights and process improvements.

The Data Operations Analyst manages data integrity and operations, supports data conversion for mergers and acquisitions, and documents policies and processes.

The role involves interpreting, validating, and structuring private equity investment data, collaborating with teams, and communicating with investment managers, while improving internal processes and data standards.

The Data Support Analyst will provide support for project tools and data, manage project financials, and prepare management reports.

The Sr Data Systems Analyst will conduct data analysis, develop business intelligence solutions, and lead projects while mentoring the team.

The Data Modeler or Analyst role involves modeling data using Oracle and Erwin, focusing on data warehousing with fact and dimension tables. Requires 5-7 years of relevant experience.

The Sr. Data Analyst will utilize industry knowledge to analyze data, develop solutions, and support customers globally, focusing on delivering high-quality IT services.

Seeking a Sr. Data Analyst with 5+ years in data analysis, strong SQL skills, and healthcare industry experience. Responsibilities include data mapping and analysis.

Seeking a Sr. Data Analyst with 5+ years experience in data analysis, particularly in the healthcare sector, with strong SQL skills.

The Data Modeler/Analyst will collect, organize, and interpret data. Responsibilities include data profiling, modeling, visualization, and documenting mappings, alongside ensuring data governance compliance.

Build reliable data models and semantic layer for AI-powered analyses. Support Product, Finance, and Customer Success with SQL-based analytics, BI dashboards, and stakeholder storytelling. Standardize data team processes, prioritize work, and collaborate across company to enable data-informed decisions.

Partner with Sales, RevOps, Marketing, and Customer Success to connect the full revenue funnel. Produce GTM insights using advanced analytics, SQL, and BI tools; communicate findings to stakeholders; standardize Data team processes; mentor analysts and lead data-driven initiatives to drive business outcomes.

The Senior Data Analyst will manage client-facing analytics, build dashboards, partner with Customer Success, and leverage AI tools for reporting.

Own the conversion of raw alternative datasets into scalable, AI-ready data products. Define methodologies, metric definitions, and guardrails for AI-driven insights. Partner with engineering, product, and customers to expand use cases, ensure data quality, validate changes, and manage incidents to deliver reliable, explainable data products at scale.

Lead analytics and evaluation for search and retrieval systems: define measurement strategies, run experiments, analyze ranking and user behavior, build dashboards, ensure data quality, and partner with product, data science, and engineering to improve relevance and retrieval performance.

The Data Operations Analyst will manage projects supporting AI model development, collaborating with teams to ensure project success and deliver high-quality datasets.

Build, QA, and maintain custom audience segments and automations; run complex SQL to extract, analyze, and validate large datasets; ensure data quality and policy compliance; manage requests end-to-end in Salesforce; troubleshoot and document technical issues; advise stakeholders on audience design; contribute to process and tooling improvements across global teams.

Lead development of scalable audience and measurement products across brands and platforms. Build dashboards, KPI frameworks, and analyses to quantify content discovery, AI-driven consumption, identity resolution, and advertising effectiveness. Partner with Product, Engineering, and business stakeholders to translate large-scale data into actionable insights and drive enterprise decision-making.

Lead data cleansing, validation, and certification for ERP data conversion. Produce auditable validation results, triage and resolve data issues, document evidence for certification, and collaborate with cross-functional teams to ensure data quality throughout the conversion lifecycle.

Lead reporting and analysis across product, call center, and marketing; manage enrollment and revenue reconciliation; produce partner and carrier reports; analyze member engagement and plan performance to surface actionable insights.

Senior analyst to integrate and map Charles River Data (CRD) with accounting and data management systems. Requires 6-8 years BA experience with Charles River architecture and data model, and participation in back-office migration or Charles River upgrade projects.

Senior Technical Analyst role requiring 8-10 years in data warehousing. Responsible for data modeling, applying SDLC processes, designing/working with ETL or reporting tools, and strong database concepts to support enterprise data warehouse initiatives. Full-time, long-term position based in Herndon, VA.

Lead data analysis and architecture efforts for healthcare insurance projects: gather requirements, design source-to-target mappings and data models, enforce enterprise data standards, support data profiling/conversion, and participate in solution planning and estimations. Mentor/train others and translate business drivers into technical requirements across the SDLC.