Top Data & Analytics Jobs

Develop financial, strategic, pricing, forecasting, and operational models; analyze complex datasets; build dashboards and recurring reports; validate data; and translate findings into actionable recommendations. The Senior Analyst partners with Sales, Pricing, Operations, Finance, and senior leaders to support strategic decisions, identify risks and opportunities, automate reporting, and manage multiple analytical projects.

Leads business intelligence and data strategy by integrating organizational systems, analyzing large datasets, and delivering actionable insights. Advises leadership and revenue-generating teams on attendance, visitor experience, fundraising, profitability, and operational improvements. Oversees data modeling, visualization, process design, project execution, budgeting, stakeholder collaboration, mentoring, and data-driven decision-making.

Designs, builds, and maintains scalable Databricks and PySpark data pipelines; develops Python and SQL transformations; identifies insights from ambiguous datasets; and ensures data quality, governance, documentation, and reliable delivery. Collaborates with stakeholders and cross-functional teams to integrate data into applications and dashboards, troubleshoot pipeline issues, and support a Department of Defense Navy client.

Owns production data systems end to end, including data models, ETL and API integrations, applications, platform maintenance, data quality, governance, and technical debt. Supports OPSDB and exploration operations, improves reliability and alerting, documents systems, collaborates with cross-functional and nontechnical stakeholders, and mentors junior analysts. The role also supports procurement and inventory initiatives, works with geologists, and requires occasional international travel to exploration sites.

Own Marketing’s reporting and analytics layer by building executive dashboards, defining KPIs, modeling data across GTM systems, and establishing governance and trusted sources of truth. Partner cross-functionally to measure funnel performance, attribution, campaigns, pipeline, and ROI. Help evaluate and develop AI-powered analytics, conversational reporting, automated insights, and intelligent visualization while translating complex data into actionable recommendations for leadership.

Leads and supports database design, development, administration, optimization, and maintenance. Develops database schemas, parser and loading software, queries, scripts, and macros while aligning structures with system architecture. Directs requirements fulfillment, data organization, storage and retrieval, and complex database systems using cloud methodologies. Requires extensive Oracle platform experience, Linux and Bash skills, a current poly clearance, and substantial database engineering experience.

Collects and analyzes internal and external data to identify trends, opportunities, and risks. Develops dashboards, reports, and visualizations for leadership; monitors KPIs; partners with advisors to answer business questions; and supports strategic planning through forecasting, modeling, and scenario analysis.

Maintains vendor process maps and pricing data, coordinates database server and application installation and configuration, troubleshoots database errors, manages user access and data distribution, provides data management support, and communicates with vendor IT teams.

Conducts proactive and responsive prospect research to evaluate donor capacity, affinity, and engagement. Develops research profiles, due diligence reports, briefings, prospect lists, and analytical materials supporting fundraising and stewardship. Maintains prospect records, analyzes wealth screening and institutional data, monitors relevant developments, and advises development staff on portfolio management and cultivation strategies. Also supports research tools, documentation, training, and process improvements while handling confidential information.

Build and operate large-scale data ingestion pipelines powering research and trading platforms. Own pipeline quality, reliability, performance, and data health; collaborate with traders, quantitative researchers, and data owners; optimize compute, storage, and SLAs; migrate pipelines to modern platforms; and implement tools to detect and resolve source-data quality issues.