Top Data & Analytics Jobs

Builds and maintains scalable data pipelines and reusable datasets in Databricks. Ingests, validates, transforms, and models structured and unstructured data using Python, PySpark, and SQL. Integrates warehouse and cloud analytics systems, supports Tableau and Spotfire reporting, improves reliability and performance, and implements testing, monitoring, documentation, and CI/CD. Collaborates with technical and business stakeholders while providing technical guidance, code reviews, and mentorship.

Manages qualitative and quantitative data across proprietary and third-party consultant databases. Ensures data quality, maintains investment strategy content, conducts research and analysis, supports automated reporting, prepares consultant database responses and RFPs, and coordinates with relationship managers, investment specialists, content teams, and marketing data teams.

Analyze paid media, CRM, organic demand, conversion funnels, and service-line performance for Aspen Dental. The role synthesizes data, evaluates marketing incrementality, measures experiments, develops ROAS and diminishing-return frameworks, supports forecasting, and recommends channel and market investment decisions. The analyst partners with marketing, media, finance, technology, call center, and other teams to embed analytics into daily decision-making.

Build and maintain dbt data models and pipelines for billing, payments, usage, and revenue data. Ensure data accuracy, reconciliation, integrity, and timely delivery while defining metrics and monitoring systems. Develop dashboards and self-service data products, support finance data operations, and collaborate with Billing Engineering, Finance, Accounting, and Product teams. Influence billing data architecture and engineering roadmaps.

Designs, develops, and maintains Power BI dashboards, reports, visualizations, and data models. Translates stakeholder requirements into reporting solutions, integrates SQL, Excel, and cloud data sources, optimizes queries and report performance, ensures data accuracy and access controls, and supports data governance. Provides documentation, user guidance, and training while continuously improving analytics solutions.

Conduct deep industry research on home services companies, design surveys and data studies, analyze datasets, and publish quarterly reports for executive audiences. Build profiles of key executives and use AI workflows to create personalized briefs. Support CEO and CRO meetings, refine research based on feedback, and recommend new data sources and tools.

Supports master data management through data cleansing, validation, auditing, profiling, governance documentation, data quality reporting, system migration support, testing, and root-cause analysis. Collaborates with data stewards, IT teams, and business stakeholders to maintain accurate enterprise data and a reliable single source of truth.

Own and expand Ramp’s AI spending research, including the Ramp AI Index, new adoption and ROI metrics, international analysis, and customer-facing insights. Produce research reports, visualizations, presentations, dashboards, and interactive tools for finance leaders. Translate data into recommendations for budgeting and AI strategy, collaborate with growth teams on distribution, and communicate findings through writing, events, and executive engagement.

Establishes and maintains master data standards, including entity resolution, matching, survivorship, identifiers, authoritative sources, and golden records. Partners with business and technical teams to validate implementations, resolve data quality issues, embed requirements into systems and integrations, and lead remediation efforts. Sets monitoring and stewardship practices, evaluates vendor approaches, maintains governance documentation, and communicates data quality and remediation progress through cross-functional leadership.

Six-month fellowship analyzing alternative data to identify business and industry insights for investment professionals. Responsibilities include developing sector expertise, producing written and visual research, collaborating with data science, engineering, sourcing, and compliance teams, and translating complex findings for varied audiences. Fellows gain exposure to discretionary investing and may be considered for permanent placement after completing the program.