Top Data Engineer Jobs in Minneapolis, MN

The Data Visualization Developer will create and support dashboards in Power BI, develop SQL scripts, perform regression testing, and troubleshoot existing scripts.

The Senior Data Engineer will design and build data models, manage data pipelines, improve data quality, and collaborate with teams to deliver reliable data solutions for the company.

The Data Integration Engineer will manage data integrations and ETL processes for healthcare data, ensuring accuracy and accessibility for business users.

As a Senior Data Engineer, you will design and optimize data pipelines, enhance system efficiency, and collaborate with teams to drive health outcomes using large healthcare datasets.

The Staff Data Engineer will design data architecture, develop scalable data pipelines, ensure data quality, and lead governance practices while collaborating across teams.

As a Senior Data Engineer, you will enhance the data lakehouse, optimize data workloads, perform complex transformations, and develop frameworks to improve delivery velocity, focusing on cybersecurity solutions.

Contract Senior Data Engineer to implement, configure, and optimize Adobe Experience Cloud solutions, design and maintain data pipelines and orchestration, support CDP ingestion and activation, validate data quality and tracking implementations, and collaborate with cross-functional teams to deliver analytics and customer experience solutions. Remote US freelance role (1099 or W2) for a short-term engagement.

Design, build, and scale reliable batch and real-time data pipelines and warehouses. Partner with engineering, data science, and business teams to define data models, improve observability, optimize storage and querying, and evangelize data engineering best practices across the company.

Lead architecture and implementation of scalable data systems and pipelines from ingestion to delivery. Own ambiguous, high-impact integrations, improve data quality and reliability, adopt AI-augmented engineering, mentor engineers, and collaborate with Product, ML, and customer teams to ship production solutions.

Design, build, and maintain scalable batch and streaming data pipelines and analytics-ready data models. Implement cloud (primarily AWS) data platform solutions, data ingestion, transformation, orchestration, and observability. Embed data quality, governance, security, and metadata/lineage practices. Partner with architecture, analytics, and application teams to enable self-service analytics, reporting, and downstream use cases while driving platform evolution and engineering best practices (CI/CD, testing, documentation).

Design, build, and maintain scalable, fault-tolerant streaming data architectures and real-time pipelines using Kafka, MSK, and Kinesis. Implement stream processing, monitoring, security, IaC, and CI/CD. Collaborate with data teams, provide technical leadership, and optimize latency, throughput, and cost for real-time analytics and downstream systems.

The Senior Data Engineer will maintain and improve data infrastructure, design ETL processes, and create high-performance pipelines for analytics and AI initiatives using SQL and Python in cloud environments.

Lead data engineering for a healthcare scheduling platform rebuild: map legacy multi-TB schema, design target schema, build translation layer (views/materialized views and write mappers), ensure data consistency during parallel systems, plan per-tenant cutover with verification and rollback, tune DB performance, instrument data quality/lineage/audit, and mentor engineers.

Lead design and delivery of production data platforms, pipelines, and analytics. Architect Snowflake/Databricks solutions, build ETL/streaming ingestion, implement dbt transformations, data quality, observability, and governance, support BI and AI/ML feature/data pipelines, and mentor engineers while driving DataOps and platform best practices.

Build and maintain a near real-time financial dashboard by integrating market and forecast APIs, automating financial models, and crafting clear visual narratives using Flourish and Canva. Collaborate with design and marketing partners, ensure data accuracy and performance, and optimize data flows across multiple feeds.

The Senior Data Engineer will design and maintain data pipelines, write production-grade Python and SQL code, and support AI initiatives while collaborating across teams.

Design and build scalable batch and streaming data pipelines, lead architecture for Lakehouse platforms, and mentor junior engineers while optimizing data quality and performance.

Lead data engineering strategy and design scalable data ecosystems. Build and maintain distributed ETL pipelines, enforce data governance (PII/PHI), improve developer efficiency, mentor engineers, and align technical work to business objectives while delivering reliable, monitored production systems.

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.

Lead and define architectural solutions for data pipelines, mentor teams, optimize ETL/ELT processes, and ensure data governance in a client-facing environment.

As a Senior Data Engineer, you will manage data pipelines, ensure data quality, partner with teams for data-driven decisions, and improve the data platform while maintaining data integrity.

The Senior Data Engineer will create and manage data pipelines, ensuring data quality, collaborating with teams for data-driven decisions, and evolving the data platform.

As a Data Operations Engineer, you will manage partner data lifecycle, ensuring data quality and performance while collaborating with teams to enhance data integration processes and guide architecture decisions.

The Senior Data Analytics Engineer analyzes and delivers business intelligence solutions, builds data pipelines, and collaborates with clients to meet their data-driven needs.

The Staff Data Engineer will enhance the data ecosystem at WeightWatchers by developing data pipelines, collaborating cross-functionally, and ensuring data quality while leading projects and technical initiatives.