Top Data Engineer Jobs in Minneapolis, MN

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, apply data modeling and DAGs, use Databricks, Airflow, and Hadoop, and collaborate with clients to deliver actionable insights.

Lead design and implementation of data infrastructure, pipelines, and integrations using cloud platforms. Manage teams and client accounts, ensure data quality, security, and compliance, deploy scalable solutions (Databricks, Snowflake), mentor junior staff, and identify data-driven business opportunities.

As a Senior Associate in Data Engineering at PwC, you will design and implement data architecture strategies, analyze complex issues, mentor junior members, and build client relationships while ensuring adherence to project standards.

As a Senior Manager in Data Engineering, you will lead teams to design data architectures, develop data solutions, manage client engagements, and ensure compliance with data governance policies.

As a Manager in Managed Services, you'll lead data ecosystems projects, mentor juniors, manage client accounts, and deliver data strategies to optimize operations and drive insights for clients.

Lead data engineering projects, develop and implement data pipelines and architecture strategies, manage data quality, and mentor team members at PwC.

The Principal Data Engineer will lead data engineering efforts on public cloud, design scalable solutions, build data pipelines, and drive deliverables with a high level of technical expertise in relevant technologies.

As a Data Engineer at Edmunds, you will architect and maintain data platforms for analytics and AI/ML, ensuring scalable, reliable data processing and supporting cross-functional collaboration.

The Principal Data Engineer will design, implement, and lead data solutions, working closely with teams using technologies like Azure Databricks and Kafka, mentoring junior engineers, and improving CI/CD and DataOps practices.

The role involves building large, scalable analytics pipelines, defining data models, integrating data, and collaborating on data architecture and strategies.

The Data Engineer will help build modern data infrastructure, designing ETL pipelines, modeling datasets, and collaborating with teams for improved data quality and accessibility.

The Data Engineer will build and maintain data pipelines, optimize workflows, manage infrastructure, and enhance pipeline observability while collaborating with teams for effective data delivery.

As a Data Engineer II, you will build, scale, and optimize data platforms, focusing on ETL/ELT pipelines, and collaborate with data scientists and AI engineers to support data-driven applications and insights.

Design, build, and maintain scalable batch and streaming data pipelines and data models using Python/PySpark, Snowflake, and cloud platforms. Optimize performance, implement orchestration (Airflow), enforce data governance/metadata standards, create data quality frameworks, support CI/CD and DevOps, monitor production pipelines, and collaborate with stakeholders to evolve the enterprise data platform.

Design, build, and maintain scalable data pipelines and AI-powered solutions using Python, Spark, Scala, Kafka, Databricks, and cloud data services. Focus on KTLO activities including vulnerability remediation, tool/version upgrades, data security, platform stability, performance tuning, and automation. Collaborate with cross-functional teams to model data, optimize queries, and support streaming and workflow orchestration (Airflow).

The Senior Data Engineer manages Oracle databases, performs data migrations, conducts performance tuning, and develops automation. This role also includes on-call support and collaboration with teams.

Design, build, and maintain scalable data architectures and ETL/data pipelines. Ensure data quality, implement data processing solutions, collaborate with cross-functional teams, provide technical guidance, and drive best practices for reliable, efficient data delivery.

The Senior Data Engineer will design, develop, and maintain ETL workflows and pipelines, optimize performance, troubleshoot ETL processes, and ensure data quality in a healthcare setting.

Build, test, and operationalize complex data pipelines and solutions on cloud platforms. Analyze and transform data, ensure data governance, security, and quality, troubleshoot defects, and collaborate across teams to support analytics, ML/AI, and business intelligence needs.

Design, build, and maintain scalable data pipelines and models; collaborate with analysts and data scientists to provision prepared datasets; implement data quality, governance and monitoring; recommend technologies; lead root-cause analysis, code reviews and testing; mentor teammates and support production data environments.

The Senior Data Engineer will develop and optimize ETL pipelines and data applications, ensuring high-quality data delivery and addressing production issues effectively.

Design, build, test, and operationalize data pipelines and solutions. Analyze data sources, apply transformations and quality controls, resolve incidents, and collaborate with teams to deliver data products supporting analytics, BI, and AI/ML use cases.

The Senior Staff Data Engineer will design scalable data systems, lead technical direction, optimize data platforms, and ensure data quality and performance for Observability & Insights.

The Data Engineer will develop and maintain data pipelines, ensuring data accessibility and quality while collaborating with various teams. Responsibilities include architecting data solutions on GCP, managing ETL processes, establishing data governance, and building CI/CD pipelines for automation.

The Data Engineer will lead data modeling efforts for Navy and DoD projects, integrating engineering methodologies, overseeing data solutions, ensuring quality and alignment with project goals, and collaborating with cross-functional teams.