Senior Data/AI Engineer

Cardinal Health

1d•$123,400 - $176,300•Remote

About The Position

The Senior Data/AI Engineer is a senior individual contributor on the Data & AI Engineering team responsible for leading the design and delivery of data and AI solutions across our Lakehouse and SQL Server environments. The responsibility of the role is to own projects from problem framing through scoping, architecture, prototyping, and production deployment. Work spans modern healthcare data platforms and AI engineering, including medallion architecture (bronze/silver/gold), Delta Lake, T-SQL ETL, and natural language AI capabilities such as NLP/NLU, retrieval-augmented generation (RAG), document-level LLM extraction, and agentic frameworks applied to EHR/EMR, practice management (PM), pharmacy, claims, and clinical note data.

Requirements

8+ years in Data Engineering, Software Engineering, or Analytics, with a proven track record of taking 0-to-1 initiatives from concept to production.
Bachelor's degree in Computer Science, Machine Learning, Analytics, Engineering, or a related field highly preferred; Master's degree a plus.
3+ years of hands-on experience with Databricks and/or Snowflake, a major cloud platform (Azure, GCP, or AWS), PySpark, Spark SQL, and Delta Lake fundamentals (ACID, MERGE, OPTIMIZE/ZORDER, schema evolution).
Experience with T-SQL on Microsoft SQL Server (or PLSQL/Oracle), including stored procedures, views, and functions, and navigating large codebases.
Proven experience (with healthcare data context) deploying NLP/NLU and modern AI/LLM-based systems (e.g., RAG, document-level extraction) from research through production, covering chunking, retrieval, prompting, evaluation, monitoring, and cost/performance tuning.
Experience working with diverse healthcare data (EHR/EMR, PM, pharmacy, claims, clinical notes) while adhering to HIPAA, PHI-handling, and multi-tenant data isolation standards.
Strong technical leadership skills, capable of scoping and leading initiatives, driving architectural decisions, mentoring, and collaborating across product, clinical, analytics, and platform teams.
Demonstrates intellectual curiosity, a bias for investigation, and the ability to research and prototype novel approaches.
Expertise in performance tuning for Spark/Databricks and SQL Server, including plan analysis, partitioning, indexing, and query optimization.
Solid understanding of data modeling (dimensional/normalized) and modern ETL/ELT design patterns, including incremental loads and medallion Lakehouse architecture.
Strong grasp of SDLC, Git, CI/CD (Azure DevOps, GitHub Actions, or similar), automated testing, data quality, observability, and rigorous code/design reviews.
Hands-on experience using Claude Code, Codex, or similar AI-assisted development tools.
Excellent written and verbal communication skills, able to influence technical decisions and translate complex concepts across diverse stakeholders.

Nice To Haves

Experience with agentic frameworks is a plus.

Responsibilities

Lead the design and delivery of data and AI solutions across Lakehouse and SQL Server environments.
Own projects end-to-end, from problem framing and scoping through architecture, prototyping, and production deployment.
Develop and implement modern healthcare data platforms and AI engineering solutions, including medallion architecture (bronze/silver/gold), Delta Lake, and T-SQL ETL.
Design and build natural language AI capabilities such as NLP/NLU, retrieval-augmented generation (RAG), document-level LLM extraction, and agentic frameworks.
Apply AI and data engineering solutions to diverse healthcare data, including EHR/EMR, practice management (PM), pharmacy, claims, and clinical notes.
Drive 0-to-1 initiatives from concept to production, defining problems, exploring solution spaces, and delivering measurable value.
Research and prototype novel approaches to complex problems, operating effectively in ambiguous environments.
Serve as a technical lead on cross-functional initiatives, establishing project-level technical direction.
Drive engineering and code quality standards within the team.
Mentor mid-level engineers, fostering their growth and development.
Partner with product, clinical, analytics, and platform teams to translate ambiguous requirements into robust, production-ready systems.
Operate fluently across Databricks and major cloud platforms (Azure, GCP).
Leverage modern AI-assisted development tooling (e.g., Claude Code, Codex) to accelerate delivery.