Top Senior Level Data Engineer Jobs in Washington DC,

As a Staff Machine Learning Engineer at Handshake, you will lead a small team to enhance AI products and infrastructure, focusing on Generative AI and Recommendations. You will develop machine learning systems, design partnerships across teams, and drive technical direction while ensuring high-quality execution and user-centered solutions.

As a Staff Analytics Engineer, you will design and build data pipelines and infrastructure to enhance operational performance. Collaborating with data scientists and engineers, you'll ensure clean, accessible data and contribute to data strategy focusing on quality and governance. Mentor junior team members and optimize data systems for business operations.

The Lead Data Engineer will oversee the design, construction, and optimization of data orchestration and pipeline architecture. Responsibilities include implementing ELT/ETL processes, managing data architecture, supporting multiple teams, and mentoring junior engineers. The role demands a hands-on approach to build data systems while contributing to the company's data strategy.

As a Senior Data Engineer, you will develop and enhance data infrastructures, improve data quality, and design systems for performance and reliability. You'll partner with product managers and data teams, build batch and streaming pipelines, and ensure effective data governance. You will also drive technical projects and optimize workflows.

The Sr. Global Privacy and Data Protection Counsel at Pendo will oversee global data privacy needs, ensure compliance with privacy regulations, lead legal activities related to Pendo’s privacy program, and provide counsel to various business units. The role requires collaboration with product and engineering teams, as well as training the legal department on data privacy regulations.

The Data Engineer will support a healthcare project by designing and delivering interactive dashboards and reports, integrating core data sources, and optimizing legacy systems. Responsibilities include developing ETL pipelines, creating actionable insights, and defining funnel metrics.

Design and implement enterprise-wide data strategies, manage data engineering assets, collaborate with cross-functional teams, ensure data integrity and security, develop data models, and lead data governance initiatives.