Top Hybrid Data Engineering Jobs

The Junior Quantitative Data Analyst will develop data pipelines, automate processes using Python, manipulate data with SQL, and ensure data integrity while interpreting financial data.

The Lead Infrastructure Engineer will manage infrastructure projects, utilize technical expertise, and collaborate across teams to enhance technology processes.

The Lead Data Architect will design and implement data architecture solutions, collaborate with cross-functional teams, and develop strategies for data integrity and completeness.

The Director will lead the Data Engineering and Analytics department, managing analytics teams, driving improvements, and communicating with senior leadership while overseeing data projects and standards.

The Data Engineer will build datasets and pipelines for marketing and sales reporting, collaborating with various teams to support data needs and ensure scalable solutions.

Develop and implement advanced algorithms, apply statistical techniques, collaborate with clients, assess technologies, and mentor team members.

The Data Operations Manager will lead a team of Data and Software Engineers, optimizing data infrastructure for business intelligence and analytics while ensuring data reliability and accessibility across the organization.

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.

The Senior Manager, Data Engineering oversees data engineering efforts, focusing on intelligent foundations and experiences. They are responsible for leading teams and optimizing data solutions.

Develop and productionize a next-gen Dispatch System, build predictive models, automate processes, and lead a small team in optimizing operations.

The Data Engineer will architect and deploy Big Data environments, manage data pipelines, and ensure data integrity across the organization.

The Data Analytics Engineer will enhance Salesforce analytics, translate business requirements into technical specifications, maintain data flows, and ensure data quality and reporting standards.