Top Data Engineer Jobs in Minneapolis, MN

As a Data Engineer, you will design and maintain data pipelines, build data storage systems, and support analytics workflows, ensuring data reliability and performance. You will collaborate with engineers to define data structures and improve data management practices.

Design and implement scalable ETL/ELT pipelines for structured and unstructured data, ensure data quality for bot training and real-time decisions, integrate data with conversational AI platforms, monitor and maintain voice bot systems, implement logging/monitoring, optimize data flows, and collaborate with AI/ML, DevOps, and compliance teams.

Designs, builds, and maintains complex data systems for analysis and reporting, ensuring efficient data processing for decision making.

The Data Engineer II designs and maintains scalable data pipelines using AWS and Databricks, optimizing ETL/ELT workflows, collaborating with teams to deliver high-quality datasets, and supporting AI/ML use cases through data preparation and validation.

The Data Engineer will build and operationalize data solutions, analyze data sources, ensure data governance and quality, and support analytics across teams.

As a Data Engineer at Travelers, you will design and operationalize complex data solutions, support analytics through data pipelines, and collaborate with teams to deliver insights from data.

As Lead Data Engineer, you will guide a team, manage the data platform, and oversee the development of ML infrastructure and feature stores.

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

The Data Engineer will develop and optimize data pipelines, manage data architecture, support cross-functional teams, and ensure data security and integrity.

The Data Engineer at Netflix builds systems for efficient data processing and modeling, collaborating with various teams to empower analytical insights and product features.

The role involves analyzing data security, designing Databricks components for access control, and collaborating on architecture documentation.

Design, build, and maintain scalable, reliable data pipelines and services. Write well-tested Python and SQL code, work with orchestration (Airflow), containers, and cloud infrastructure. Collaborate cross-functionally to deliver data products and improve development processes.

Build and maintain Databricks-based ETL/ELT pipelines, transform and model data, optimize workflows, monitor and troubleshoot pipelines, and collaborate with cross-functional teams.

Develop and deliver data infrastructure and rapid prototypes to support data science and analytics. Collaborate with data scientists and business partners to define requirements, build and test data solutions, mentor teammates, and support predictive modeling and enterprise data assets from prototyping through production.

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.

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

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

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.

The Data Engineer will enhance the Enterprise Data Warehouse, modernizing ETL processes, optimizing data transformations, ensuring data quality, and providing production support while collaborating with cross-functional teams.

Design, build, and maintain scalable Databricks-based data pipelines; lead migration/rehydration of ~500 PowerBI reports; implement CI/CD for data assets; optimize ETL/ELT and establish DevOps/versioning/testing best practices.

Lead and mentor a data engineering team to design and operate scalable ETL/ELT pipelines and Snowflake data warehouse solutions using Python, DBT, Matillion, and AI tools; establish standards, ensure data quality and governance, and collaborate with analytics, product, and BI stakeholders to deliver production-ready data platforms.

The Senior Data Engineer at Unchained will design and implement data pipelines, integrate APIs, ensure data governance, and mentor team members while focusing on accuracy and security.

The role involves writing and deploying scripts for data collection, transforming data sets, diagnosing bugs, and collaborating with other engineers using agile principles.

The Data Engineer I supports the Data Engineering Team by running queries, manipulating data, documenting processes, and resolving data issues.

The Principal Data Engineer will lead the Data Resolution team, focusing on complex data challenges using Spark, system architecture, and mentorship, to optimize graph data pipelines.