Top Data Engineer Jobs

Design and build scalable data solutions, develop real-time data pipelines, maintain ETL processes, and promote effective development methodologies.

As a Snowflake Data Engineer, you'll design, build, and maintain data infrastructure using Snowflake, focusing on governance, quality, and performance optimization. You'll collaborate with stakeholders to operationalize data use cases and implement key data strategies.

Lead projects, design cloud-native data pipelines, manage technical debt, enhance data warehouse, and mentor team while supporting AI and business insights.

The Senior Research Engineer will curate large datasets, automate data pipelines, optimize queries, and support data-driven research impacting business outcomes.

As a Senior Data Engineer, you will design, develop, and support data solutions, collaborate with Agile teams, and mentor others while working with cloud technologies.

As a Data Engineer III, you will develop data solutions, lead projects, mentor peers, and ensure efficient data pipelines within cloud architectures.

The Data Engineer will design and maintain data infrastructure, develop scalable pipelines, and collaborate with stakeholders to ensure effective data solutions at DISA.

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

The Data Engineer will design, implement, and maintain data pipelines, support automated data analysis, ensure high data quality, and collaborate with teams.

As a Data Engineer, you'll design and implement data lifecycle strategies, ensure data integrity, optimize solutions, and collaborate across teams to enhance data management.

The Data Engineer will clean, manage, and analyze datasets, automate ETL processes, and collaborate with traders and software engineers to derive insights.

As a Data Engineer at Figma, you'll build and maintain scalable data pipelines, optimize data models, and collaborate with teams to ensure timely data delivery.

The Data Engineer will design and maintain data pipelines using AWS tools, develop AI models for automation, and ensure data quality and governance.

The Senior Consultant, Data Engineer will engage clients in data engineering projects, focusing on data warehousing, ETL development, and data modeling using Databricks and Python.

The Data Engineer will work on data migration and transformation in an Azure environment, developing designs, securing data transfers, and conducting data profiling.

The Data Engineer II will design, develop, and improve analytical data models and pipelines, collaborating across teams to meet data needs.

The Data Engineer designs and manages data systems, focusing on backend integration, ETL processes, data visualizations, and system security while mentoring team members and engaging with stakeholders.

Design and build secure data pipelines, lead data architecture, collaborate across teams, ensure data quality, and mentor other engineers.

The Senior Data Engineer will build and optimize data pipelines, ensure data integrity, and collaborate with stakeholders to meet business requirements while implementing best coding practices.

As a Senior Lead Data Engineer, you'll design and implement data solutions, lead a team of developers, and drive transformation at Capital One.

Design and build scalable, low-latency streaming data platforms, implement data pipelines using big data technologies, and ensure data accuracy.

As a Senior Data Engineer, you will design and implement data solutions, leveraging big data technologies while collaborating with Agile teams to deliver powerful experiences for customers.

The Senior Data Engineer II will design, build, and maintain a data LakeHouse platform, focusing on data pipelines, modeling, and AWS infrastructure development.

As a Senior Data Engineer, you will design and implement data solutions, collaborate with teams, and work on big data technologies to drive transformation at Capital One.

As a Senior Data Analytics Engineer, you will design data models, collaborate across teams, improve data infrastructure, mentor others, and lead complex analytics projects to drive business outcomes.