Data Engineer - AI, Agents, & Context - Revenue Cycle (Associate)

About the Role

Day-to-day, you will be responsible for executing key parts of the AI context platform, including unstructured ingestion, embeddings, retrieval, and semantic layers. Your work will have a direct impact on the company's ability to drive growth, enhance performance, and sustain leadership in the markets it serves.

The role sits within a team that is dedicated to helping healthcare organizations build innovation capabilities and accelerate key growth initiatives. As such, you will be working with a talented group of professionals who are passionate about using technology to improve patient outcomes and reduce the cost of care.

What You Will Do

• Build and contribute to the AI context platform, focusing on unstructured ingestion, embeddings, retrieval, and semantic layers
• Implement end-to-end pipelines, including ingestion, parsing/chunking, enrichment, embeddings, vector indexing, and retrieval/serving
• Develop and maintain patterns for incremental refresh, backfills, re-embeddings, deduplication, and lineage across unstructured sources
• Contribute to retrieval quality improvements, including query strategies, hybrid search, and metadata filtering
• Deliver semantic and governed data products, implementing semantic layers that power BI and agent reasoning
• Ensure datasets and indexes are documented and reusable, following established data contracts and context contracts for AI inputs
• Support reliability and performance across assigned workstreams, including monitoring, alerting, runbooks, and incident response
• Contribute to cost and latency optimization across Snowflake and vector infrastructure
• Apply security-by-design patterns, including RBAC/ABAC, PII redaction, retention controls, and audit logging
• Follow established guardrails for AI access to enterprise knowledge in coordination with Security/Legal/Compliance

What We Are Looking For

• Bachelor's Degree in computer science, engineering, or a related field of study
• 3-6 years of experience in data engineering or data platform roles, with strong hands-on delivery
• Strong SQL and Python skills (or Scala/Java), with solid production engineering experience
• Experience with data pipelines, including ingestion, processing, and retrieval
• Knowledge of AI and machine learning concepts, including embeddings, retrieval, and semantic layers
• Experience with cloud-based data platforms, including Snowflake and vector infrastructure
• Strong collaboration and communication skills, with the ability to work with cross-functional teams
• Experience with security-by-design patterns and data governance principles

Nice to Have

• Experience with healthcare data and analytics, including clinical and claims data
• Knowledge of data visualization tools, including Tableau or Power BI
• Experience with agile development methodologies and version control systems, including Git
• Certification in data engineering or a related field, including AWS or Google Cloud

Benefits and Perks

• Competitive salary and benefits package
• Opportunity to work with a talented team of professionals who are passionate about using technology to improve patient outcomes
• Collaborative and dynamic work environment, with a focus on innovation and growth
• Professional development opportunities, including training and education programs
• Flexible work arrangements, including remote work options and flexible hours
• Access to the latest technologies and tools, including cloud-based data platforms and AI solutions
• Recognition and reward programs, including bonuses and stock options

• Tip: Highlight your experience with data pipelines, including ingestion, processing, and retrieval, and be prepared to provide examples of your work.
• Tip: Showcase your knowledge of AI and machine learning concepts, including embeddings, retrieval, and semantic layers, and explain how you have applied these concepts in previous roles.
• Tip: Emphasize your ability to collaborate with cross-functional teams, including data scientists, product managers, and engineers, and provide examples of successful projects you have worked on.
• Tip: Be prepared to discuss your experience with security-by-design patterns and data governance principles, and explain how you have applied these principles in previous roles.
• Tip: Research the company and the role, and be prepared to ask informed questions during the interview process.
• Tip: Highlight your passion for using technology to improve patient outcomes, and explain why you are interested in working in the healthcare industry.
• Tip: Be prepared to provide examples of your experience with cloud-based data platforms, including Snowflake and vector infrastructure, and explain how you have optimized performance and cost in previous roles.