Top Data Engineer Jobs in Minneapolis, MN

As a Senior Associate, you will develop and implement IBM MDM solutions, mentor junior team members, and manage data quality frameworks while providing insights from data analysis.

Develop and productionize a next-gen Dispatch System, build predictive models, automate processes, and lead a small team in optimizing operations.

The Data Engineer will design and maintain ETL pipelines and data storage solutions, collaborating with cross-functional teams to ensure efficient data processing and delivery.

The Data Engineer II will build and operationalize data solutions, manage data quality, collaborate across teams, and mentor team members while serving as a technical lead in an agile environment.

As a Data Engineer, you will build and optimize data pipelines, manage ETL workflows, and ensure efficient data access and quality within the infrastructure.

Design and deploy data processing pipelines, analyze data to extract insights, and develop software systems for data management and privacy.

The Data Architect designs data flows, defines standards, ensures data quality, and collaborates on data strategies while integrating advanced technologies.

The Data Engineer will build ETL pipelines and data infrastructure, ensure data quality, and implement modern data warehousing for analytics improvements, while collaborating with stakeholders across teams.

As a Power BI Developer, you'll transform Qlik dashboards into Power BI, ensuring accuracy, usability, and collaboration with internal teams while optimizing visualization performance.

This role involves building and maintaining data pipelines, developing data models, and ensuring data discoverability while enabling scalable analytics on blockchain data.

The Senior AI Data Engineer will design and maintain datasets for AI models in cybersecurity, ensuring data quality and relevance while collaborating with teams.

As a Data Engineer, you will design and implement a data platform, maintain data pipelines, work with Airflow and BigQuery, and ensure data compliance while collaborating with teams.

As a Data Engineer, you'll design and maintain data platforms, develop data pipelines, collaborate with teams, and ensure data quality for diverse stakeholders.

The Senior Data Engineer will maintain ChowNow's data platform, enhance data pipelines, work with data scientists, and improve data quality and accessibility, contributing to executive decision-making and business growth.

The Data Engineer will manage data ingestion in Salesforce, standardize lead data, ensure data quality, and optimize integration workflows.

As a Data Engineer at Thatch, you'll develop data infrastructure, build ELT pipelines, and collaborate across teams to provide analytics insights.

The Data Engineer will build scalable privacy-centric data frameworks, engineer data pipelines, and ensure compliance with privacy regulations at Netflix.

The Data Engineer will architect and expand data products for Netflix's Ads business, developing data pipelines, collaborating with analysts, and ensuring data quality.

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.

Lead the evolution of SimplePractice's data stack, building scalable systems for analytics, reporting, and product insights in a fast-paced environment.

The Data Engineer will design, develop, and optimize large scale data pipelines and ensure effective data delivery for cross-functional teams.

As a Data Engineer, build efficient data processing systems, model data to support analytics, and collaborate with teams to enhance Netflix's data-driven culture.

Design, develop, and manage data infrastructure for internal and client projects, focusing on large-scale data pipelines, APIs, and cloud deployments.

The job involves leveraging AWS and Snowflake for data engineering tasks within a technology-focused company, requiring US residency.

The Data Analytics Engineer builds and maintains analytics tools and data pipelines, operationalizes machine learning models, and optimizes performance for decision-making insights.