Top Senior Level Data Engineer Jobs

In this role, the Senior Manager of Machine Learning will lead a team focused on developing machine learning solutions for fraud prevention in the financial services sector. Responsibilities include team management, performance evaluation of models, and collaboration with various teams to enhance customer experience and business profitability.

The Principal Data Management role involves designing and implementing a long-term enterprise data management and governance program. Responsibilities include developing data quality applications, managing relationships with federated data governance groups, and partnering with external vendors to enhance the program's maturity.

As a Senior Machine Learning Engineer at TrueML, you'll architect and implement ML infrastructure, develop production-grade ML pipelines, and maintain systems for real-time and batch decision-making. You'll collaborate with data engineers and data scientists to scale algorithms and ensure robust deployment of machine learning models.

The Senior Research Data Steward manages data and metadata for defined domains, ensuring data integrity and compliance. Responsibilities include collaborating with data owners, establishing data management plans, and promoting best practices in data governance. The role involves communicating with various stakeholders and providing training to enhance data management processes.

As a Senior Programmer/Analyst, you will develop software solutions to enhance enterprise systems and support reporting and analytics for geological data. You will work in Agile teams, provide subject matter expertise, analyze database structures, reverse engineer legacy applications, and support data needs through SQL operations.

The Big Data Engineer will create and optimize data engineering pipelines, support data and cloud transformation initiatives, and work with stakeholders to deliver enhanced functionalities. The role involves utilizing big data processing frameworks and maintaining automated ETL processes while collaborating with software engineers and data scientists.

Design and build the next generation library for deep learning within the firm. Empower researchers to iterate faster and perform experiments that were not possible before. Work with HPC experts to optimize workflows and deliver improvements in training speed and cost savings.