Top Hybrid Data Engineering Jobs

The Analytics Engineer will build data infrastructures, create dashboards, define metrics, structure datasets for AI projects, and foster insights across company functions.

The Senior Data Engineer will develop scalable data pipelines, drive automation, enforce standards in Big Data, and collaborate with stakeholders on data solutions.

The Portfolio Chief Engineer will lead design and implementation of Data and Analytics Systems, working with customers and engineering teams to generate innovative solutions, engage in business development, and ensure technical excellence in large-scale information management.

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

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

The Lead Data Engineer delivers end-to-end data solutions, mentoring engineers, designing data architecture, and enhancing data pipelines across the organization.

The Data Engineer II will build and maintain data pipelines and warehouses, ensure data quality, and collaborate with cross-functional teams to support business intelligence and machine learning efforts.

As a Lead Data Engineer, you will collaborate with Agile teams, develop technical solutions, and enhance cloud-based data warehousing to empower financial services for customers.

The Principal Data Platform Engineer leads the design of data architectures, implements data platform patterns, and optimizes system performance, ensuring data strategy operates at scale.

The Principal Data Engineer will design, implement, and lead data solutions, working closely with teams using technologies like Azure Databricks and Kafka, mentoring junior engineers, and improving CI/CD and DataOps practices.