Top Data & Analytics Jobs

Owns enterprise data governance activities, including metadata management, data cataloging, data quality rules, lineage, profiling, report certification, PII handling, and governance workflow automation. Partners with data stewards, IT teams, business stakeholders, and senior leaders to improve data integrity, regulatory compliance, reporting quality, and governance processes. The role also supports training, stakeholder workshops, process improvement, and mentoring of less experienced professionals.

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.

The job description is incomplete. Based on the available text, this role appears to support pathology data activities within a clinical laboratory environment.

Analyzes statistical, financial, and claims data; develops automated reporting files; tests and debugs systems; translates carrier requirements into business and technical requirements; monitors reporting processes; resolves complex technical issues; and supports customers, vendors, insurers, and actuarial teams.

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.

Build and maintain Warp’s analytics infrastructure, canonical data models, ETL and reverse-ETL pipelines, data quality systems, and self-service analytics tools. Define product and business metrics, analyze experiments, support pricing and revenue analytics, and conduct research into user behavior, growth, engagement, and churn. The role partners broadly across product, engineering, growth, revenue, and go-to-market teams while incorporating AI agents into data workflows.

Build and maintain Siro’s go-to-market data infrastructure, including data pipelines, API integrations, CRM and warehouse synchronization, enrichment workflows, and reporting models. Ensure GTM data is clean, reliable, documented, and actionable. Partner with GTM leaders to execute automation roadmaps, analyze funnel performance, evaluate tools and datasets, and recommend improvements that increase sales development effectiveness.

Own operational processes in Addepar, onboard complex client relationships, build alternative transaction histories, create alternative assets, and produce recurring and ad hoc portfolio reports. Analyze investment data, troubleshoot reporting issues, improve processes, document data governance, manage reporting projects, and develop industry insights. The role requires expertise with Addepar, Canoe, Excel, and alternative investment products.

Analyzes digital product and healthcare data to define metrics, build dashboards and visualizations, assess ROI and business impact, ensure data quality, and communicate actionable insights to senior stakeholders. Collaborates with Digital, Data, and business teams while working with Epic and non-Epic datasets, SQL, Power BI, Excel, and Agile/Scrum processes.

Supports the enterprise data and analytics platform by building Microsoft Fabric lakehouses, warehouses, pipelines, semantic models, and Power BI reporting. Integrates D365, manufacturing, warehouse, supply-chain, IoT, and operational data; develops SQL and DAX solutions; implements data quality, governance, security, monitoring, and documentation; and troubleshoots production issues. The role also supports AI-enabled analytics and collaborates with business teams, vendors, and technical stakeholders in a manufacturing environment.