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.

Develops and maintains enterprise Power BI reports, dashboards, datasets, data models, and pipelines. Translates stakeholder requirements into reliable, governed analytics solutions and identifies opportunities for automation and integration. The role applies data visualization, storytelling, SQL, data warehousing, Power Platform, and Azure Data Services expertise while ensuring role-based access, reporting accuracy, audit readiness, and stakeholder adoption. This is a hybrid office role requiring collaboration with business teams and adherence to established standards.

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.

Analyze payment accounts and transactions to identify fraud and credit risk, develop scalable risk strategies, and design solutions including ML features and manual review workflows. Collaborate with Engineering, Product, Data Science, and Operations to mitigate fraud across geographies, payment methods, and products. Educate Stripe users about business risks and prevention strategies.