Top Data Engineer Jobs

Design and maintain high-quality data pipelines, develop DBT models, collaborate with analytics and data science teams, and optimize data operations for scalability.

The Customer Data Integration Specialist will architect integrations, ensure data quality, manage projects, and collaborate with various teams for a unified Customer 360 view.

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

The Senior Data Acquisition Engineer will develop web crawling technologies, enhance data quality, and collaborate on data product development.

The Data Platform Operations Engineer will automate and operate the Enterprise Data Platform ensuring reliability and performance while managing Snowflake and Fivetran resources.

Lead Data Engineer responsible for designing and maintaining data pipelines, managing data systems on cloud platforms, and providing technical leadership.

Design and build data products in a data mesh architecture, optimize ETL/ELT pipelines using AWS Glue and PySpark for real-time reporting and analytics.

As the first Data Engineer, you will manage data ingestion, architecture, and quality for our algorithmic trading team, ensuring high-performance datasets.

Seeking a Senior Data Engineer to develop ETL pipelines, ensure data quality, and integrate new data sources in a FinTech startup.

The Senior Staff Data Engineer will design scalable data platforms and pipelines, mentor other engineers, and drive innovative data solutions to enhance business value.

The Senior ETL Developer is responsible for developing solutions for data warehousing, coding ETL programs, and executing data workflows for reporting, using various Azure tools.

The role involves building data platforms and pipelines, integrating AI solutions, and collaborating with product owners to address complex client issues.

The role involves designing and maintaining Alteryx workflows, integrating with Microsoft tools, developing SQL databases, and collaborating with stakeholders for data accuracy and optimization.

The Lead Data Engineer will manage initiatives across Advanced Analytics, support cloud migration, oversee operational automation, and collaborate with stakeholders on data solutions.

Design, build, and maintain scalable data architectures using Databricks on AWS or Azure, ensuring data integrity and optimizing workflows.

As a Data & Automation Engineer, you'll build data platforms, design data models, manage datasets, and optimize data pipelines for analytics and decision-making.

Design and develop data models, pipelines, and practices to support a digital app, ensuring reliable and scalable data procurement.

Lead the development of a modern Data Warehouse platform in the cloud, owning data ingestion pipelines, data models, and infrastructure while mentoring junior engineers.

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.

As a Data Analytics Engineer, you will build and optimize the data layer, transforming business requirements into reliable datasets using SQL and dbt, while collaborating with analysts and engineers.

As a Senior Data Engineer, you will build and maintain data pipelines for analytics, collaborating with teams to implement data models and ensure data quality.

The Data Analytics Engineer will develop data models, create dashboards, maintain data pipelines, and collaborate with various teams to improve analytics practices.

As a Senior Data Engineer, you will design and build data products, establish best practices, and lead technical initiatives in data architecture and workflows within the single-family rental industry.

Design and optimize data pipelines using Python and SQL. Mentor junior engineers, improve CI/CD processes, and troubleshoot data issues.

The Senior Data Engineer will develop scalable data pipelines, manage efficient data workflows, mentor team members, and enhance data quality while collaborating with various teams to meet data needs.