Top Data & Analytics Jobs

Administers and supports organizational databases within the IS Data Management team. Diagnoses application, system, and workload performance issues; manages user data access and database authority; reviews database development; conducts performance and volume testing; coordinates with vendors; and reports project progress to stakeholders.

Conduct software category research, develop product taxonomies and review questions, contribute analysis to buyer guides and reports, write thought-leadership articles, and support review quality control. The role requires strong writing, research ability, technology enthusiasm, attention to quality, and collaboration in a fast-paced startup environment.

Analyzes logistics business and cost data, identifies cost drivers and improvement opportunities, improves cost data governance, and develops optimization initiatives. The role evaluates warehousing, transportation, procurement, labor, lease, and consumables costs; performs root-cause analysis; coordinates cross-functional projects; tracks savings and efficiency gains; and supports continuous improvement across business operations.

Own marketing analytics across attribution, channel efficiency, experimentation, incrementality, unit economics, GTM analytics, lifecycle marketing, and reporting. Define marketing data models, build dbt models and Looker reporting, evaluate campaign and channel performance, and guide budget allocation. Partner with marketing leaders and executives to turn data into actionable decisions, improve measurement, and establish a trusted, data-driven marketing engine.

Analyze product and business data to guide product strategy, growth, customer experience, and experimentation. Responsibilities include funnel, cohort, retention, segmentation, monetization, dashboard, and reporting analysis; defining metrics; maintaining event tracking; troubleshooting data quality; integrating data from analytics, advertising, payment, and CRM systems; and documenting tracking plans and metric definitions.

Own social listening, cultural and competitive intelligence, organic social measurement, and campaign performance analysis. Translate qualitative and quantitative signals into concise recommendations that guide content, creator, campaign, and amplification decisions. Manage partner and platform inputs, maintain benchmarks and test-and-learn agendas, track recommendation implementation, and measure business impact. Collaborate with Strategy, Creative, Influencer, Community, and Guest Experience teams to improve social performance and inform broader business decisions.

Manage the health, performance, reliability, and cost of customer Snowflake and Databricks environments. Responsibilities include customer onboarding, account and warehouse setup, permissions, data ingestion, query optimization, cost reporting, incident response, escalation support, and automation using Python and Terraform. The role also advises customers and internal teams on data platform best practices and participates in on-call rotations.

Designs and governs data architecture for internal applications and business intelligence systems. Owns database architecture, data modeling, warehouse migration, schema standards, and operational versus analytical workload separation. Builds and monitors batch and event-driven pipelines using SQL, PostgreSQL, and Python; supports ETL/ELT across varied sources. Advises technology teams on data-platform decisions, reporting, performance, security, recovery, and architectural tradeoffs. The role is onsite in Sacramento and requires substantial production database and pipeline experience.

Investigate production incidents using raw real-time data, identify root causes, and recommend resolutions. Build statistical system-health metrics, descriptive reports, and repeatable investigation tooling. Analyze event-driven systems during live sports events, work independently on ambiguous problems, and collaborate with data science, engineering, and trading teams. Develop and maintain production software using Python and Rust.

Supports strategic planning through business intelligence, data integration, data modeling, reporting, dashboards, forecasting, and analytics solutions. Acquires and validates healthcare claims, demographic, provider, regional, and service-line data; monitors data quality and reporting processes; troubleshoots issues; documents methodologies; and partners with BI developers and cross-functional teams to maintain scalable enterprise analytics capabilities.