Top Hybrid Data & Analytics Jobs

Lead AXS' global data engineering organization to define strategy, architecture, and roadmap for data platforms and pipelines. Own design, operation, and reliability of batch and real-time systems, data lake/warehouse, governance, security, and compliance. Build and scale a high-performing global team, partner with cross-functional stakeholders, drive operational excellence, manage budgets, and deliver data infrastructure that enables personalization, analytics, fraud prevention, pricing, and reporting.

Lead analytics and operations for BD and Marketing by designing reporting systems, conducting experiments, and providing actionable insights to drive growth and optimize performance.

Build and maintain mobile attribution and marketing data pipelines, implement postbacks to ad platforms, configure tracking (server-side GTM, pixels, CAPI), automate event audits, handle mobile privacy (SKAN/ATT/AD_ID), debug discrepancies across ad platforms/CRM/warehouse, use Python and BigQuery for validation, and partner with Growth/Product/Data to run and measure experiments.

As a Quant Researcher, you will research volatility modeling and options valuation, implementing solutions in C++ and Python for financial applications.

The role involves coordinating systems analysis and design projects, leading Agile workboards, and acting as a liaison between business units and technical teams to improve data systems through automation.

The Senior Data Engineer II will build and optimize data solutions on Axon's Corporate Data Platform, design data pipelines, mentor team members, and uphold data governance and quality standards.

The Associate Director, Business Systems will partner with teams to translate stakeholder needs into product requirements, manage backlog, and ensure successful delivery of data and analytics initiatives in the healthcare sector.

Own and evolve Stash's dbt-powered data mart and Looker semantic layer: build production dbt models, enforce data quality and freshness, define trusted metrics, partner with engineering and data science, enable self-serve analytics, improve job reliability and performance, and mentor peers to maintain trustworthy reporting for Product, Growth, Finance, and Data Science.

Lead a Finance-embedded data science and analytics team, own metric governance and single source of truth, maintain data models and pipelines for FP&A (including Anaplan feeds), improve financial data quality and automation, evolve finance data architecture with DBT and Snowflake, and partner with Finance leadership and the CFO to bring AI and automation into finance processes.

Build and maintain marketing-focused data pipelines, analytics instrumentation, and attribution systems (server-side tagging, conversion APIs). Create data products, dashboards, and integrations across web, iOS, and paid channels to enable reliable, privacy-safe marketing measurement and self-serve analytics.