Top Data & Analytics Jobs

Develop and maintain SAS programs for cleaning, linking, transforming, and analyzing large health insurance claims datasets. Create cohorts, analytic datasets, variables, descriptive statistics, and reports for health policy research. Collaborate with investigators, statisticians, clinicians, and senior programmers across projects involving maternal, child, and mental health. Support data quality checks, statistical analyses, meetings, manuscripts, and research reporting.

Build and maintain reusable analytical data products, canonical entities, data marts, semantic layers, and governed metrics across business domains. Establish modeling, documentation, quality, lineage, and change-management standards; improve data reliability, self-service analytics, and production governance. Partner with Data Platform, Trust, Data Science, Applied AI, and business stakeholders on orchestration, observability, access controls, feature tables, model outputs, and shared metric definitions. Remain hands-on with SQL, Python, testing, code reviews, documentation, and technical coaching.

Analyzes business and customer requirements to define metrics, measurement frameworks, and scalable Tableau dashboards. Partners with stakeholders across life sciences, healthcare, and sales organizations to deliver consistent, data-driven insights. Documents BI standards, ensures metric accuracy and security compliance, demonstrates expertise in relevant data sources, and manages dashboard requests through a Jira backlog while meeting delivery timelines.

Coordinates research and analytics initiatives supporting economic development, neighborhood planning, and downtown engagement. Responsibilities include maintaining databases, dashboards, and development maps; analyzing market, transactional, survey, and travel behavior data; supporting reporting and communications; engaging stakeholders; assisting with events; and providing administrative and cross-team support. The role requires strong data management, analytical, organizational, communication, and quality-control skills, along with proficiency in Excel and related GIS, CRM, and visualization tools.

Lead the design and delivery of scalable batch and real-time data pipelines across AWS, Snowflake, PostgreSQL, MongoDB, dbt, and Kafka. Establish standards for data modeling, governance, security, testing, observability, and reliability. Build trusted datasets and semantic layers for BI, analytics, AI/ML, RAG, and LLM applications. Drive platform optimization, data integration, MDM, technical strategy, mentoring, and cross-functional collaboration.

Own the technical infrastructure supporting Spotify’s revenue growth programs. Build and maintain dbt models, BigQuery pipelines, dashboards, reports, and LLM-enabled data workflows. Monitor pipeline health, resolve data issues with engineering and Insights teams, and translate sales needs into reliable data products that improve prioritization, outreach, and advertiser growth.

Analyze complex datasets, build Power BI dashboards and reports, write SQL, and use Python with Pandas and NumPy for data manipulation and automation. Work extensively with Snowflake, validate and reconcile data, define KPIs, support forecasting and AI-driven analytics, and translate stakeholder requirements into analytical solutions. Present insights and recommendations while collaborating with business, data engineering, and data science teams to improve reporting, data quality, governance, and self-service BI.

Analyzes specialty-products markets, customer pricing, contracts, forecasts, and strategic performance metrics. Maintains pricing tools, supports growth action plans and business planning, manages agreements and nickel hedges, and prepares market and customer reports and presentations. Coordinates with field representatives, product managers, sales teams, and customers to support commercial activities and corporate reporting.

Senior Business Analyst leading discovery and requirements definition for Data & AI initiatives. Translates business needs into user stories, technical and functional requirements, and acceptance criteria; coordinates stakeholders, data engineers, BI developers, and product owners through delivery. Manages intake, prioritization, sprint progress, and communication while promoting Agile practices, MVPs, process consistency, and data-driven decision-making. Requires experience with analytics environments, Power BI, Tableau, project tracking tools, SDLC, and data concepts.

Support GEOINT and Multi-INT production at NASIC by developing structured data schemas, ensuring adherence to intelligence community standards, identifying useful data sources, and maintaining data consistency through QA/QC scripts. Collaborate with analysts, data scientists, engineers, and government stakeholders while providing technical guidance, briefings, and documentation.