Top Hybrid Data & Analytics Jobs

Analyze business performance data and convert it into actionable insights, board decks, leadership reports, and all-hands presentations. Own recurring reporting, identify trends and risks, improve reporting processes, and partner with senior stakeholders across Commercial, Operations, Finance, and Marketing to shape clear business narratives and support strategic decisions.

Leads the Emerging & Established Marketing Analytics insights function, building and coaching an analyst team while owning full-funnel performance narratives across brands and markets. Translates experimentation and measurement outputs into recommendations, delivers executive-level insights, manages senior stakeholders, establishes scalable analytical frameworks, and partners cross-functionally with Marketing, Product, Finance, Data Science, BI, and Operations.

Lead and mentor a product analytics team that diagnoses product performance, evaluates launches, defines trusted KPIs, and drives strategic decisions. Oversee rigorous experimentation, causal inference, cohort analysis, metric governance, and telemetry standards. Partner with Product, Engineering, Marketing, Growth, Design, and Finance leaders to translate analysis into recommendations. Promote AI-native workflows using tools such as Claude Code while ensuring analytical quality, code validation, and clear executive communication.

Owns the health, performance, and evolution of Oracle, PostgreSQL, and MongoDB database platforms across Azure and OCI. Responsibilities include database architecture, performance tuning, HA/DR, cloud infrastructure, CI/CD automation, observability, cost optimization, and real-time production support. The role partners with DevOps, Infrastructure, and Software Engineering teams and participates in on-call incident response for mission-critical warehouse management workloads.

Develop and optimize data pipelines, ingestion and transformation jobs, incremental datasets, and automated data flows on modern data platforms. The role designs scalable data solutions, applies DevOps and data engineering principles, improves pipeline architecture, supports governance and data quality, and provides operational documentation. It also involves cross-functional collaboration with platform, governance, analytics, and data science teams, while mentoring early-career professionals.

Design, build, and maintain scalable batch and streaming data pipelines, cloud infrastructure, and the Enterprise Data Hub. Partner with stakeholders to productionize ingestions, ensure data quality, implement metadata/catalog solutions, mentor junior engineers, and support analytics and ML workloads using cloud and big-data tooling.

Leads complex business and data analysis across multiple sources to identify insights, risks, and opportunities. Partners with stakeholders to define business needs, improve processes, develop reports and dashboards, and recommend solutions. Coordinates project workstreams, monitors outcomes, supports change initiatives, and communicates findings to management. Ensures accurate, timely, well-documented deliverables aligned with business priorities, policies, and regulatory requirements.

Designs and builds scalable analytics data models, consumption layers, and transformation pipelines supporting BI, reporting, and AI applications. Partners with stakeholders to translate business needs into technical requirements, improves data architecture and quality, applies software engineering best practices, evaluates data tools, troubleshoots issues, and optimizes data infrastructure and workflows.

Develops and manages dashboards, reports, data models, semantic layers, and analytics solutions for Sales, Marketing, and Distributor Development. Translates business needs into actionable insights, ensures data quality, supports self-service analytics, and provides user training and support. The role also owns customer classification, performs ad hoc analysis, contributes to enterprise Business Intelligence initiatives, and improves reporting processes.

Own the strategy and architecture for a scalable, multi-cloud data platform across Revv and AirPro. Integrate Azure SQL Server data with AWS, Fivetran, dbt, and Snowflake pipelines; build trusted dbt models; connect Salesforce and ERP systems; and establish governance, quality, ownership, and compliance foundations. Partner with analytics, finance, sales, product, and engineering leadership to translate business needs into reliable data assets and customer-facing products.