Top Remote Data Engineer Jobs in Ann Arbor, MI

Design and maintain scalable data pipelines, collaborate with cross-functional teams, manage data architectures, optimize Snowflake performance, and enhance data workflows.

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

Design and optimize data pipelines, work with structured/unstructured data, ensure data quality for analytics, and collaborate with data scientists.

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.

Analyze and develop data solutions, lead projects, translate business requirements, provide support for ETL processes, and mentor junior team members.

The Senior Data Analytics Engineer develops business intelligence solutions using the Microsoft Analytics stack, collaborates with clients, and delivers scalable data solutions.

Design, build, and maintain scalable data infrastructure in the cloud using AWS services and Infrastructure as Code to ensure data reliability and performance.

The intern will assist the Data Operations team in optimizing data workflows, developing automation scripts, and maintaining data systems while gaining hands-on experience.

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 & Analytics Engineer will model and serve data, improve architecture, and collaborate with teams to sustain the data strategy, requiring 5+ years of experience.

The Senior Data Engineer will manage and transform data pipelines, implement changes in Snowflake, monitor costs, and resolve data issues.

The role involves developing AI applications, building data pipelines, maintaining analytics infrastructure, and collaborating with sales teams to enhance go-to-market strategies using data-driven insights.

The role involves building and optimizing data pipelines, modeling datasets, applying machine learning techniques, and supporting data strategies. Candidates should have experience with Python, data lakes, warehousing, and related technologies.

The Data Quality Engineer ensures the accuracy and reliability of healthcare data pipelines, drives QA automation, and collaborates with cross-functional teams to resolve data integrity issues.

The Senior Data Engineer will focus on ingesting and curating satellite imagery and geospatial data, building data pipelines, and mentoring junior engineers, while ensuring performance and scalability.

As a Staff Data Engineer, you will enhance and modernize data platform infrastructure, manage data processing platforms, and mentor junior engineers.

As a Lead Data Engineer, you'll optimize data workflows, manage data engineering projects, mentor junior engineers, and ensure robust data solutions meet business needs.

As a Senior Data Engineer, you will build data infrastructure, develop CI/CD pipelines, and create entity resolution systems, focusing on large-scale data processing and analytics.

The Data Visualization Engineer will create data storytelling products, enhancing user experiences with intuitive data representations and collaborating closely with stakeholders on visual applications.

As an Associate Engineer in Data Science, you will leverage data analysis and machine learning to solve complex problems and develop inspiring digital products.

Nagarro seeks an Associate Principal Engineer in Big Data to leverage extensive IT experience for strategic organizational value. The role values self-starters and innovation.

As a Senior Data Engineer, you'll design, build, and optimize data infrastructure while collaborating with teams to enhance data flow and integration across platforms.

The role involves building and optimizing data pipelines, managing data integration, supporting analytics, and collaborating with cross-functional teams to enable data-driven decisions.

Lead the architecture and development of scalable data pipelines, mentor team members, and align data engineering practices with business objectives in a complex technical environment.