Top Senior Data & Analytics Jobs in Minneapolis, MN

Leads enterprise data architecture and engineering for modern cloud data platforms. Designs scalable architectures, data models, pipelines, Airflow orchestration, quality frameworks, governance, and observability. Provides hands-on technical leadership across Snowflake, Databricks, Python, Spark, and SQL environments while mentoring engineers, establishing standards, optimizing performance, and aligning data capabilities with analytics, reporting, and AI/ML objectives.

Designs and maintains scalable data pipelines, integration workflows, data lakes, and engineering platforms using AWS, InterSystems Ensemble, HL7, CCDA XML, and MySQL. Responsibilities include transforming and validating clinical data, optimizing queries, supporting analytics, solving complex client data challenges, and mentoring junior engineers. The role also involves client collaboration, critical thinking, Agile delivery, and adherence to professional and technical standards.

Leads People Analytics consulting engagements that help HR and business leaders make workforce decisions. Frames business questions, guides quantitative analysis, develops actionable recommendations, presents findings to executives, and measures adoption and impact. Partners with HR Business Partners, promotes governed self-service analytics, and ensures responsible use of employee data and AI. Requires fluency in SQL and analytics tools, plus expertise in workforce topics including retention, engagement, performance, planning, and organizational effectiveness.

Designs, builds, administers, and supports cloud data architectures, databases, schemas, metadata repositories, ETL processes, and analytic models. Leads data quality, governance, troubleshooting, testing, automation, reporting, dashboards, and infrastructure design. Collaborates with Agile teams to translate business requirements into technical capabilities and supports decision-making for Audit and business management. The role is full-time onsite at an eligible Federal Reserve location and requires extensive security screening.

Design, build, and maintain scalable ETL/ELT pipelines and data warehouse architecture. Partner with cross-functional teams to define KPIs, ensure data quality and governance, own billing data infrastructure, and deliver dashboards and analytics for leadership while mentoring peers.

Partner with Account Management to deliver data-driven planning, whitespace and pipeline models, revenue and budget reporting, rep-level analytics, and forecast improvements. Validate Salesforce data, reconcile budgets and forecasts, measure campaign and pipeline outcomes, and provide executive-ready insights and budget recommendations to improve deal outcomes and guide resource allocation.

Leads the design, development, and implementation of scalable data pipelines, APIs, cloud-based integrations, and Customer Data Platform solutions. Builds unified customer data ecosystems supporting analytics, personalization, and enterprise integration. Responsibilities include data modeling, Lakehouse and API optimization, governance, privacy compliance, CI/CD automation, monitoring, troubleshooting, documentation, and cross-functional collaboration. Requires extensive experience with Python, SQL, REST APIs, cloud platforms, data integration tools, CDPs, and modern data engineering architectures.

Build, deploy, and operationalize data pipelines and solutions supporting AI, machine learning, and business intelligence. Responsibilities include data transformation, cleansing, governance, security, quality management, source analysis, testing, incident resolution, and defect remediation. The role collaborates across teams, supports data products, educates users, and applies software engineering and DevOps practices to deliver reliable analytical data solutions.

Defines and evolves enterprise data architecture supporting analytics, reporting, governance, integration, and AI capabilities. Designs scalable Lakehouse and Medallion architectures, data models, contracts, APIs, and event-driven integrations. Establishes governance standards and trusted data products while aligning platform investments with business and regulatory needs. Leads modernization initiatives, develops data strategy and roadmaps, supports KPI frameworks, mentors technical talent, and guides distributed engineering teams.

Leads complex healthcare analytics projects using clinical, administrative, claims, and related datasets. Develops advanced SQL queries, analytical methodologies, cohorts, outcomes, and segmentation approaches; investigates data anomalies; translates client needs into analytic requirements; validates deliverables through quality assurance; and collaborates with consultants, statisticians, and subject matter experts to produce actionable insights for strategic decisions, clinical quality improvement, and real-world evidence.