Top Hybrid Data & Analytics Jobs

Lead product analytics to inform product strategy and growth: run funnel, cohort, retention, segmentation, monetization, and experimentation analyses; define success metrics; build dashboards and reports; validate and maintain event tracking; unify data from Amplitude, ad platforms, payments and CRM; document metrics and tracking plans.

Lead Holman's Marketing Analytics function to deliver data-driven insights, governance, and reporting across Snowflake, Databricks, Power BI and other platforms. Advise senior leaders on media investment, attribution, forecasting and KPI frameworks; manage and mentor analytics staff; prioritize projects, enforce QA and automation, and integrate multi-source data for enterprise ROAS and channel performance measurement.

Lead a small team of Digital Brand Analysts to drive digital growth for assigned brands through advanced reporting, analytics, drop-ship optimization, vendor relationship management, and profitability analysis. Build dashboards, translate data into recommendations, partner cross-functionally, and drive initiatives that improve operational and financial performance.

Lead design and delivery of an enterprise Azure Databricks Lakehouse platform, migrating from Azure SQL Server. Set data platform strategy, mentor data engineers, ensure cloud-native ETL/ELT, reliability, observability, and support analytics/AI/ML. Manage portfolio, budget, vendors, and stakeholder alignment to deliver a single source of truth for insurance domains.

Designs, builds, and maintains scalable batch and streaming data pipelines, data warehouses/lakes, and ETL/ELT processes. Collaborates with BI, Data Science, and Architecture teams to model data, validate sources, ensure data quality, optimize performance, and enable analytics using cloud and big-data technologies (AWS, Snowflake, Databricks, Spark, Kafka).

Lead development and operations of geospatial data pipelines and lakehouse systems. Migrate orchestration to Prefect, extend sources and transforms, optimize Postgres and Iceberg stores, build observability and AI-agent readiness, and integrate cross-team tooling with product and ML teams.

Lead quantitative analyses of loan originations and portfolio performance to identify credit risks and improvement opportunities. Build multivariate/predictive models, conduct diagnostic and funnel analyses, measure costs/benefits, design monitoring and controls, present recommendations to VP-level stakeholders, and drive hands-on implementation using SQL, Python, Excel, AI tools, and financial modeling.

As the Founding Data Lead, you will establish the analytics function, manage high-volume data, and provide insights to inform business decisions.

The Staff Data Scientist will drive data-informed monetization strategies across subscriptions, advertising, and virtual currencies, collaborating with product and engineering teams and defining success metrics.

The Sr. Product Analyst will manage data analysis processes, providing insights into user behavior and business performance to drive growth decisions, while mentoring junior analysts.