Top Remote Data & Analytics Jobs in Minneapolis, MN

Design, build, and maintain scalable batch and streaming data pipelines, improve data modeling and governance, contribute to enterprise data architecture, and collaborate with cross-functional teams to ensure reliable, high-quality data for analytics and operational use.

Build, operate, and optimize large-scale data pipelines and warehouse schemas. Own Airflow orchestration, AWS-based data security (Lake Formation), automated data quality, and production incident resolution. Partner with stakeholders, mentor engineers, and drive DataOps best practices for performance, cost efficiency, and governance.

Client-facing solution architect leading Azure data platform pre-sales: discovery, solution design, scoping, and SOW/proposal development. Architect modern data platforms (Fabric, Synapse, Databricks, ADLS), integration/orchestration (ADF, pipelines, CDC), data modeling, governance, security, and AI/GenAI enablement. Partner with sales and Microsoft for co-sell pursuits, lead workshops, and guide delivery teams to implement governed, production-grade data foundations that enable analytics and responsible AI at scale.

QA/Business Analyst responsible for developing and executing automated and manual tests, validating ETL/data pipelines and integrations, querying complex relational databases, using AI tools for anomaly detection and test generation, leading requirements gathering and maintaining traceability, documenting defects and data quality findings, and escalating critical issues to leadership.

Lead and own the population health analytics pipeline: intake and reconciliation of claims, eligibility, and MAO-004 data; identify and reconcile care gaps and closures; deliver practice-level performance analysis and billing reconciliations; build funnel instrumentation; document, standardize, and automate pipelines with Product and Engineering. Ensure billing-grade accuracy and support program measurement aligned to CMS reconciliation windows.

Design, build, and maintain scalable data systems and ETLs on GCP; connect production data to business systems; generate analytics and ML-driven insights for GTM teams; work cross-functionally and introduce modern tools (Airflow, DBT, Presto, Hightouch).

Lead architecture and evolution of Cardlytics' AWS-based data compute platform and lakehouse. Define standards for batch, streaming, ML, and AI workloads; build semantic layer, feature store, and governance. Partner with analysts and engineers, drive CI/CD (Terraform, GitHub Actions), monitoring, security, cost governance, and incident response while mentoring teams and shaping platform strategy.

Lead day-to-day management of multi-year data projects (Neighborhood Vitality Index, Hope Starts Here). Conduct quantitative and qualitative analysis, design and analyze surveys, coordinate with external partners and internal teams, perform stakeholder outreach and engagement, and produce accessible data products and communications for non-technical audiences to inform decision-making across Detroit-area organizations.

Design, build, and operate secure, scalable cloud-native data platforms (lakehouse/data mesh) supporting batch, streaming, ML, GIS and operational workloads. Lead ingestion/transformation pipelines, distributed processing (Spark/Kafka), data governance, observability, and mentor teams while ensuring compliance in regulated environments.

Analyze conversational call flows and large datasets to optimize IVR and generative AI systems. Perform call testing, annotation, dashboard monitoring, and deliver data-driven insights and presentations to improve self-service, reduce agent handling, and enhance customer experience.