Top Data Engineer Jobs

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

The Data Engineer II will construct high-quality datasets, implement changes to data systems, write complex SQL scripts, and collaborate with stakeholders to optimize data solutions.

The Junior Data Engineer will develop data processing capabilities using Python, SQL, and Snowflake to support financial modeling and analytics within the bank.

Develop and optimize data processing infrastructure for robotic systems, enabling data access and visualization, supporting engineering teams with insights from logs.

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.

As a Data Engineer Intern at ASML, you will develop data pipeline solutions, collaborate with teams, and adopt best industry practices to meet business requirements.

As a Data Engineer Intern, you will develop data pipelines, collaborate with teams, and contribute to system improvements while focusing on customer satisfaction and industry best practices.

The Data Analytics Engineer provides data engineering solutions for biologics manufacturing, maintains systems like AVEVA PI, and promotes data analytics usage across site.

Seeking a Senior Data Engineer with expertise in Databricks, Snowflake, Python, Pyspark, and SQL to design and maintain data pipelines for banking operations.

The Senior Data Engineer will design and build complex data solutions, operate data pipelines, and guide team development while leveraging advanced ETL practices and cloud platforms to support analytics initiatives.

Responsible for designing, building, and maintaining data infrastructure, managing AWS services, and ensuring data reliability for Ecosystem Security.

Responsible for designing and maintaining data infrastructure, building ETL pipelines, managing AWS resources, and collaborating on data services to enhance security.

The Data Engineer will support NIH operations, managing complex data environments, utilizing SQL, Python, and cloud technologies, with a focus on troubleshooting and team collaboration.

Data Engineers at Endex design and maintain data pipelines for transforming financial data into insights, focusing on data quality and analytics.

Lead the development of AI solutions and data engineering strategies. Implement AI data pipelines, collaborate with teams, and ensure the reliability of data systems.

Lead the development of AI data pipelines, improve data capabilities, integrate AI solutions, mentor team members, and ensure operational efficiency.

The Data Engineer will enhance the enterprise Data Lake by integrating data sources, ensuring data accessibility, and supporting analytical teams through data ingestion, transformation, and governance in both cloud and on-prem environments.

As a Data Engineer, you will develop and manage the data infrastructure that supports HTS Media's advertising business, build ETL/ELT pipelines, and enable data-driven insights for advertisers and internal analytics.

The Senior Data Engineer designs and maintains data infrastructure, processes data from various sources, optimizes workflows, and collaborates with stakeholders to provide data insights.

The role involves developing and maintaining enterprise data pipelines, collaborating with various business units, and ensuring data quality and security standards.

The Data Warehouse Engineer manages and optimizes data warehouse environments, overseeing ETL processes, data integrations, and enterprise reporting for high performance and reliability.

As a Data Platform Engineer, you'll design and maintain scalable data systems, partner with teams on product direction, and ensure system reliability and security.

Lead architectural design for Coupang's data ecosystem, drive technical decisions, and collaborate with engineering teams on implementations to enhance data capabilities and operational excellence.

Design and maintain technical infrastructure for data analysis, collaborate with stakeholders, and develop data visualization tools.