Data Engineer, AI Pipelines

Advocate is a mission-driven technology company revolutionizing the way Americans access critical federal benefits. They are seeking a Senior Data Engineer to contribute to the data infrastructure and workflows for their AI-driven platform, focusing on optimizing data processing pipelines and ensuring data integrity and compliance.

Responsibilities:

• Researching and integrating comprehensive historical case data sets and truth sets
• Designing and implementing scalable, resilient data architectures that accommodate AI pipelines/services
• Optimizing data processing pipelines by crafting, refining, and managing ETL (Extract, Transform, Load) processes
• Implementing strict data management practices, including data validation, cleansing, and anonymization
• Supporting advanced data analysis by equipping data scientists and AI developers with the infrastructure and tools necessary for deep analytics and operational deployment of AI
• Continuously exploring and integrating the latest data engineering tools, technologies, and methodologies

Requirements:

• Advanced degree (Master's or Ph.D.) in Computer Science, Engineering, or a related field
• Extensive experience (5+ years) in data engineering, particularly in designing and implementing data systems for AI applications
• Proficiency in databases (SQL, NoSQL), big data frameworks (Spark), cloud services (AWS), and experience in developing AI pipelines and services
• Deep understanding of data modeling, data warehousing, and data integration techniques
• Experience with data quality assurance, data governance, and performance optimization
• Analytical problem-solving skills, adept at tackling complex data challenges and devising innovative solutions
• Strong team player with excellent communication abilities, capable of effectively collaborating with both technical and non-technical colleagues
• Experience working in agile development environments and familiarity with version control systems (e.g., Git)
• Familiarity with compliance standards such as HIPAA and SOC2, demonstrating understanding of critical security and privacy considerations within the healthcare and data sectors
• Knowledge of data anonymization techniques and experience working with sensitive data
• Proven track record of successfully delivering complex data engineering projects, preferably in the healthcare or public sector domains
• Proactive, self-motivated, and capable of working independently as well as part of a team
• Strong problem-solving skills, attention to detail, and the ability to thrive in a fast-paced, dynamic environment