Top Remote Data & Analytics Jobs in Minneapolis, MN

Senior individual-contributor analyst leading end-to-end, high-stakes analyses, designing dashboards and reporting, mentoring analysts, applying statistical methods and causal inference, partnering with analytics engineering to shape warehouse models, and translating findings for technical and non-technical stakeholders.

Responsible for administering, securing, tuning, migrating, and maintaining relational and non-relational databases across internal systems and client environments. The role includes capacity planning, backup and recovery, SQL optimization, performance monitoring, cloud database management, data pipeline maintenance, and troubleshooting. The administrator serves as a data management subject matter expert, supports deployment projects, recommends system improvements, presents metrics, and collaborates with development, managed services, partners, and customers.

Collaborate with business teams to define analytics needs, explore and analyze operational and financial data, build forecasts and regression models, and create dashboards and visualizations. Communicate insights to leaders, support decision-making, contribute to data modeling, metadata, quality remediation, and adhere to data governance, security, and privacy standards.

Design, develop, and maintain Customer Data Platform solutions and data pipelines to create unified customer profiles, manage identity resolution, enable audience segmentation and activation, ensure data quality and governance, and support integrations with marketing, CRM, and cloud data systems.

Build and maintain full-stack data engineering solutions supporting BioIntelliSense’s remote patient monitoring and clinical intelligence platform. The role likely involves processing health-monitoring data, enabling analytics, and supporting reporting for clinicians, patients, and employers. Specific responsibilities and qualifications are not provided in the description.

Designs, builds, and maintains scalable data pipelines, workflows, analytics solutions, and AI/ML capabilities within Palantir Foundry. Models enterprise data using Foundry Ontology, manages data assets and governance, integrates analytics tools, troubleshoots platform issues, and translates stakeholder requirements into maintainable solutions. The role also supports FAA users through documentation, training, collaboration, and ongoing platform enhancement.

Designs and scales cloud-native data platforms and ingestion pipelines using AWS, Databricks, and Spark. Builds APIs, file-upload mechanisms, ETL/ELT workflows, and Lakehouse architectures; supports SQL Server data loading and legacy C# .NET processes. Partners with analytics, software engineering, architecture, and product teams to ensure data quality and availability for reporting and machine learning. Troubleshoots pipelines and applies governance, security, compliance, documentation, and reliability best practices.

Leads digital analytics for Ford Pro Digital Product, translating stakeholder questions into measurement plans, KPIs, advanced journey analyses, dashboards, and actionable recommendations. The role uses SQL and digital analytics platforms to integrate behavioral, customer, transaction, and enterprise data. It also develops reusable analytical methods, automation, and AI-enabled workflows, partners with cross-functional teams, and presents findings to technical and executive audiences.

Build and manage end-to-end marketing data platforms on Google Cloud. Responsibilities include configuring GA4 and Google Tag Manager, creating BigQuery ingestion pipelines, managing Cloud Functions, Pub/Sub, IAM, and service accounts, developing LookML semantic models and dashboards, and orchestrating ETL and reverse ETL workflows. The role also supports CDP integrations, identity resolution, audience syncing, experimentation, data quality assurance, and lifecycle marketing analytics.

Leads analytics and reporting for Microsoft’s Cloud Solutions Provider authorization ecosystem. Develops actionable insights, dashboards, data visualizations, and self-service reporting; improves data quality, governance, standardization, and efficiency. Partners with engineering, AI, operations, and compliance teams to automate workflows, identify risks, evaluate program outcomes, and recommend improvements. Presents findings to senior stakeholders and translates business needs into technical requirements and scalable analytical solutions.