Top Senior Data Engineer Jobs in Orlando, FL

The Senior Data Engineer will maintain ChowNow's data platform, enhance data pipelines, work with data scientists, and improve data quality and accessibility, contributing to executive decision-making and business growth.

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

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.

Lead the evolution of SimplePractice's data stack, building scalable systems for analytics, reporting, and product insights in a fast-paced environment.

The Senior Data Engineer will develop and maintain data pipelines, collaborate with Analysts, and ensure high code and data quality on the Hungryroot Analytics model.

Lead design and delivery of data solutions in Adobe Experience Platform, optimize data models, mentor junior engineers, and drive strategy.

As a Data Engineer, you will design data storage systems, build ETL pipelines, optimize data reliability, and collaborate across teams, leveraging modern technologies for data management and processing.

As a Data Engineer, build efficient data processing systems, model data to support analytics, and collaborate with teams to enhance Netflix's data-driven culture.

Seeking an experienced Data Engineer to design and optimize data infrastructure, build scalable pipelines, and ensure data quality and governance.

Design and maintain scalable data pipelines, collaborate with cross-functional teams, manage data architectures, optimize Snowflake performance, and enhance data workflows.

Design and optimize data pipelines, work with structured/unstructured data, ensure data quality for analytics, and collaborate with data scientists.

Lead the implementation of AML detection pipelines using Palantir Foundry. Train team members in technical skills and oversee data architecture and maintenance.

Develop and optimize data pipelines, ensure data quality, design complex data procedures, and guide data engineering tasks. Manage real-time applications and provide insights on data processing.

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

The Senior AI Data Engineer will design and maintain datasets for AI models in cybersecurity, ensuring data quality and relevance while collaborating with teams.

As a Senior Data Engineer, you'll design, build, and optimize data infrastructure while collaborating with teams to enhance data flow and integration across platforms.

The role involves building and optimizing data pipelines, managing data integration, supporting analytics, and collaborating with cross-functional teams to enable data-driven decisions.

The Senior Data Engineer will develop scalable data pipelines, maintain production datasets, collaborate with teams, and optimize data platform infrastructure.

The Senior Data Engineer develops and maintains data pipelines, collaborates on scalable data solutions, and ensures data security via cloud services.

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

The Data Engineer will build scalable privacy-centric data frameworks, engineer data pipelines, and ensure compliance with privacy regulations at Netflix.

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

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.

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.

Lead design and implementation of scalable data infrastructure, build reliable data pipelines, collaborate cross-functionally, and influence data architecture to support analytics and operations.