Top Senior Data & Analytics Jobs in Minneapolis, MN

Provides data-driven strategic insights and business intelligence solutions for clients. Responsibilities include analyzing complex datasets, developing reports and dashboards using Oracle BI, QlikView, and BIRT, delivering recommendations, managing stakeholders, building client relationships, and collaborating with teams to optimize business performance.

Designs and develops scalable Azure and Databricks data pipelines using Python, PySpark, Spark, Delta Lake, ADF, and ADLS. Partners with AI and Data Science teams to operationalize machine learning models, feature stores, and streaming analytics. Builds reusable automation frameworks, ensures data quality, governance, security, and compliance, and optimizes batch and streaming workflows. Participates in Agile delivery, CI/CD, code reviews, production support, and responsible AI implementation.

Build trusted, secure, and repeatable data pipelines, transformations, data products, retrieval layers, and semantic data assets. Assess data quality, lineage, governance, privacy, and access constraints; support AI retrieval, embeddings, vector stores, and grounding strategies. Create test and de-identified datasets, implement monitoring and quality checks, document data assets, and ensure reliable data for AI products, control-group testing, and production handoff.

Analyzes account portfolio whitespace, pipeline, deal performance, campaign attribution, rep productivity, budgets, forecasts, and expenses. Builds models and executive reporting to improve revenue planning, forecast accuracy, and account management decisions. Partners with Account Management, Finance, Marketing, Contract Administration, and regional leaders; validates Salesforce data and translates complex findings into actionable recommendations.

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.

Analyze multi-channel fraud trends, develop data-driven insights and recommendations to prevent and detect fraud, evaluate controls and authentication strategies, support testing and implementation of fraud controls, and present executive-ready analytics to inform enterprise fraud strategy and prioritization.

Build and operationalize data solutions, pipelines, transformations, and quality processes supporting insurance pricing analytics. Analyze data sources, implement governance and security practices, test data movement, resolve defects, and collaborate with actuarial, data science, engineering, product, and business teams. The role also involves designing scalable cloud-based solutions, applying modern software engineering practices, and mentoring engineers.

Designs and governs enterprise data architecture across Azure, Microsoft Fabric, OneLake, Dynamics 365 F&O, and Dataverse. Establishes architecture standards, patterns, governance, data modeling, integration, metadata, lineage, data quality, and master data practices. Defines current, transition, and future-state architectures; guides implementation with engineering teams; evaluates technologies; resolves complex technical issues; mentors engineers; and reduces technology complexity and technical debt.

Build GCP data pipelines, ETL/ELT processes, integrations, data models, and analytics solutions. Support AI/ML development with Vertex AI and Gemini, including MLOps, prompt engineering, embeddings, and RAG experimentation. Participate in client requirements gathering, technical implementation, data governance, quality, security, monitoring, and documentation while collaborating with senior engineers and architects.

Mobile Analyst role requiring 6+ years experience. Candidate must have strong SQL skills and experience with DOMO, Snowflake, and Adobe Analytics (or similar). Position is located in Shakopee, MN, 12+ month duration, and restricted to U.S. citizens/local candidates.

Analyzes complex marketing, healthcare, and digital datasets to generate actionable insights, dashboards, campaign KPIs, ROI and attribution models. Develops predictive analytics, machine learning, AI applications, and customer segmentation models to improve HCP engagement and marketing performance. Supports data governance, accessibility, compliance, and responsible AI practices while partnering with marketing, sales, legal, compliance, and IT teams.