Top Data Engineer Jobs

The Data Engineer II will build and operationalize complex data solutions, perform analysis, collaborate across teams, and troubleshoot data issues. They will also ensure data governance, security, and quality while leveraging emerging technologies.

As a Data Engineer, you will build and operationalize data solutions, analyze data sources, ensure data quality, and collaborate with teams to deliver data products.

This co-op position involves developing data products, design and testing of data pipelines, and delivering insights from complex datasets for business decisions.

This co-op position involves developing data products and solving complex data problems using cloud technologies, SQL, and programming languages while gaining mentorship and business exposure.

As a Data Science Platform Engineer, you will enhance predictive models, develop tools for real-time predictions, expand NLP capabilities, and ensure production system performance within a collaborative team.

The Senior Databricks Data Engineer will manage client engagements, deliver ETL solutions, and improve data processing. Responsibilities include project planning, pipeline design, and collaboration with team members.

As a Data Architect, you will design, develop, and optimize data warehouses, support business intelligence applications, and lead integration efforts.

The Senior Data Engineer will design, develop, and support technical solutions, leveraging big data technologies and cloud services to drive financial empowerment solutions.

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

This role offers training for aspiring Data Engineers, focusing on technology of choice, interview preparation, and skill enhancement with guidance on OPT STEM extension.

Join an Agile team to enhance data capabilities for business intelligence, focusing on software development, data engineering, and collaboration.

The AWS Cloud Data Engineer will design, develop, and enhance AWS data environments, build scalable Data Lake solutions, and lead proofs-of-concepts into production.

The Data Analytics Engineer will manage data integration, create dashboards, analyze healthcare data, and support decision-making in a collaborative environment.

As a Senior Lead Data Engineer, you will design and develop technical solutions, lead a team, and drive cloud-based data solutions at Capital One.

The Staff Data Engineer will build and scale data pipelines, collaborating across teams to integrate AI technologies and optimize data systems for analytics.

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

The Data Engineer will design and manage data structures, build ETL workflows, and support data analytics for healthcare applications.

Responsible for developing and managing data structures and pipelines, designing ETL processes, collaborating with data science, and mentoring junior engineers.

The Associate Data Engineer develops large-scale data structures and ETL workflows, collaborates with Data Science, and improves data systems.

Develop and build data structures and pipelines, write ETL processes, collaborate with Data Science, and ensure data quality for insights.

The Data Engineer at CVS Health will develop and manage data structures, ETL workflows, and collaborate with data science teams to enhance analytics capabilities.

The Associate Data Engineer will develop data structures, manage ETL processes, and collaborate with Data Science to analyze and utilize data effectively.

The Data Engineer will develop and manage data structures and ETL workflows, collaborate with data science teams, and improve data accessibility.

The Data Engineer role involves developing and managing data structures, ETL workflows, and collaborating with Data Science to enhance data processing and reporting systems.

Develop and manage large-scale data structures, pipelines, and ETL workflows to support business applications and improve analytic processing.