Top Data & Analytics Jobs

Design and advance enterprise data and BI architecture: optimize OLTP/OLAP models, establish modeling/integration/governance standards, lead POCs, mentor teams, enable AI/ML, and guide cross-functional implementation from concept to production.

Own end-to-end market, company, and competitive research requests: scope, verify sources, track developments, and produce clear, decision-ready written briefs. Maintain research files, handle ad hoc requests with accuracy and turnaround, and help refine research processes. Support internal business needs and prepare work for potential client-facing engagements.

Analyze market and live data to set dynamic ticket prices using Uptick, build strategic pricing recommendations, communicate with clients about strategy and performance, and collaborate with BI and engineering to improve product performance.

The BI Systems Manager will own and develop Valar's data infrastructure and platform, leading a team, managing data systems, and ensuring effective reporting and analytics processes are in place as the company scales its operations.

Partner with the Growth Marketing Lead to synthesize channel performance, own KPI reporting, run LTV/CAC and cohort analyses, evaluate experiments, and translate messy data into clear, prioritized recommendations that drive marketing decisions. On-site in San Francisco, measured by the decisions your analysis changes.

Manage and grow a data engineering team, overseeing the design and maintenance of data platforms using Snowflake, dbt, and Azure. Drive best practices in data management and ensure reliable data movement and quality.

As a Data Engineer at MAI, you will develop and maintain data platforms, design ETL/ELT processes, ensure data quality, and collaborate with teams to optimize data utilization for analytics and ML applications.

The Data Engineer will build and scale Baseten's internal data platform, designing data models and pipelines while enabling self-service analytics and ensuring data reliability.

The RevOps Analytics Engineer is responsible for maintaining data infrastructure, building reliable data systems, and supporting revenue analytics through effective data modeling and ETL/ELT processes.

Manage and improve master data across customer, product, entitlement, subscription, contract, billing, and revenue domains. Configure and support MDM platform rules and workflows, integrate master data with Salesforce/CPQ/billing/ERP/data platforms, create golden records and hierarchies, support product taxonomy for CPQ, maintain entitlement/install-base data, perform profiling/cleansing/reconciliation, document mappings and lineage, and partner with Sales Ops, Revenue Ops, Finance, IT, and Governance teams.