Top Senior Data & Analytics Jobs

Analyze customer adoption, engagement, health, and churn-risk data. Define consistent metrics, build dashboards and cohort analyses, monitor onboarding and implementation performance, identify friction and success patterns, and translate findings into actionable recommendations for customer-facing teams and leadership. Collaborate with revenue operations, AI engineering, analytics, and customer teams to document metric logic and improve data-driven customer experience operations.

Own GTM performance analytics, KPI and target setting, reporting, forecasting, compensation planning, and performance reviews across Sales and Post-Sales. Identify anomalies and optimization opportunities involving conversion, churn, productivity, pricing, packaging, segmentation, channel economics, and customer quality. Partner with Finance and GTM leaders to develop recommendations, lead strategic initiatives, and ensure data integrity while translating analysis into actionable business decisions.

The M365 Platform Manager oversees the Microsoft 365 ecosystem, leading architectural direction, team development, and governance while ensuring alignment with business priorities and security standards.

Lead a GTM Analytics team supporting Marketing, Sales, RevOps, and Customer Operations. Manage embedded analysts, establish trusted reporting and QA processes, review SQL and dashboards, guide funnel, campaign, sales, support, forecasting, segmentation, attribution, and experimentation analysis, and deliver executive recommendations. Partner with GTM leaders and data engineers, coach analysts, and develop self-service analytics, automation, governed dashboards, metric documentation, and AI-assisted workflows.

Owns RTB House’s performance media measurement strategy across products. Responsibilities include defining measurement taxonomies, evaluating attribution, incrementality, MMM, and MTA methodologies, managing third-party measurement partners, developing testing playbooks, piloting identity and measurement approaches, translating insights into market-facing messaging, and training commercial teams. The role requires hands-on performance media buying or oversight experience and strong ability to communicate measurement concepts, limitations, and results to technical, executive, and commercial audiences.

Leads a team of five experienced analysts and data scientists while personally owning strategic analytics across ecommerce, health, supply chain, inventory, fulfillment, and merchandising. Partners with executives, establishes KPI and reporting standards, prioritizes the analytics roadmap, and delivers actionable business insights. The role also advances AI-native, self-service analytics capabilities, strengthens data governance and quality, and builds a high-performing analytics culture.

Designs and manages scalable data pipelines, contracts, transformation layers, and analytics models. The role focuses on data governance, observability, lineage, configuration validation, and collaboration with product engineering teams. It requires processing large datasets, integrating cloud and on-premises industrial technologies, and implementing streaming and message-queuing solutions, ideally in cybersecurity or industrial environments.

Own the design, governance, and evolution of the enterprise data lake and warehouse. Responsibilities include developing conceptual, logical, and physical data models; defining source-to-target mappings; reconciling legacy CRM and operational data; establishing data quality frameworks; administering schemas, views, access controls, and performance; and partnering with engineering and business stakeholders to support scalable, self-service analytics.

Lead the architecture and development of scalable AWS-based data ingestion, transformation, and orchestration pipelines. Build reliable data infrastructure using Python, SQL, Airflow, Lambda, ECS, SQS, and Terraform. Establish data modeling, quality, lineage, monitoring, testing, and observability practices while partnering with analysts, scientists, and backend engineers. Mentor senior engineers, guide technical decisions, and provide hands-on leadership for complex data platform initiatives.

Lead commercial analytics to diagnose sell-through, pricing, promotions, assortment, and retailer execution. Build causal and incrementality measurement, design test-and-learn, support elasticity and margin analyses, and deliver executive-ready insights and frameworks to optimize revenue, margin, and promotional efficiency across channels and retailers.