Top Remote Data & Analytics Jobs in Madison, WI

Lead the vision and execution for scalable data governance and quality across Airbnb. Architect future-proof data ecosystems, define best practices and tooling, drive cross-functional policy implementation (privacy, legal, infosec), mentor senior engineers, and influence executive strategy to embed stewardship into the data product lifecycle.

Administers and engineers Microsoft SQL Server databases for NAVSUP, including database design, development, security, performance tuning, testing, backup and recovery, documentation, release support, and outage resolution. Collaborates with application developers, manages database instances and interfaces, supports CI/CD deployments, conducts quality audits, and ensures compliance with DoD and DoN policies.

Owns end-to-end business analytics for Neutrogena categories, delivering performance reporting, dashboards, competitive intelligence, and weekly business storytelling. Analyzes POS, share, retailer, and competitive trends to identify growth opportunities and risks. Partners with marketing, finance, customer strategy, and commercial teams on planning, forecasting, and business reviews. Translates complex data into executive-ready insights and narratives that influence strategic priorities and action plans.

Lead insurance risk analytics engagements for property and casualty carriers. Responsibilities include product demonstrations, regulatory filing guidance, pilot and proof-of-concept design, loss ratio and model validation analysis, client project management, discovery sessions, and translating insights for actuarial, underwriting, and executive audiences. The role also develops AI-assisted workflows and provides customer feedback to product teams.

Build and deliver Azure and Microsoft Fabric data solutions for clients. Responsibilities include developing data pipelines with Azure Databricks, Data Factory, Synapse Analytics, and Fabric; writing SQL, Python, and PySpark; supporting data integration, testing, deployments, troubleshooting, CI/CD, and infrastructure management. The role involves consulting with client stakeholders, collaborating with architects and developers, and delivering modern data platforms and reporting solutions.

Lead and scale companywide analytics for a DTC marketing business: own marketing measurement, financial forecasting, retention/LTV modeling, data architecture, reporting, and the analytics team. Set analytics strategy, oversee data engineering roadmap, build dashboards, apply statistical and ML methods, and translate insights into executive-level decisions.

Analyzes paid media performance across the full funnel, connecting spend and platform metrics to applications, enrollment, student lifetime value, and ROAS. Builds attribution frameworks, Databricks data pipelines, Power BI dashboards, semantic models, and advanced DAX reporting. Supports marketing mix modeling, experimentation, web analytics data quality, forecasting, governance, and workflow automation. Translates complex analytics into strategic recommendations for executive and cross-functional stakeholders.

Leads enterprise data platform architecture, engineering standards, technical decisions, and development of scalable data products. Designs batch and streaming systems, governance, observability, security, and reliability practices. Partners cross-functionally, mentors engineers, drives modernization and migrations, and establishes reusable patterns for data modeling, orchestration, quality, and platform operations.

Lead the architecture and implementation of scalable, secure cloud data platforms for Nokia’s photonic integrated circuit operations. Build high-performance batch and streaming pipelines, enterprise data models, quality and observability frameworks, DataOps automation, governance, and AI-ready data foundations. Enable trusted self-service analytics and AI-assisted exploration while leading and mentoring product engineering teams and driving technical excellence.

Leads Relation Insurance’s enterprise data engineering and analytics function, owning data strategy, architecture, pipelines, governance, quality, reporting, and AI-enabled workflows. The role requires hands-on development in SQL, Python, and PySpark, executive communication, technical team leadership, lakehouse architecture, Power BI modeling, production support, and secure data management. The director also directs AI coding agents, builds LLM-powered workflows, establishes engineering standards, and delivers reliable data products aligned with business priorities.