Position Description:
We're looking for those individuals-the creative thinkers and innovation seekers-who are content with nothing short of changing the world. Discover the endless opportunities within the Medical College of Wisconsin (MCW) and be inspired by the work we can do together to improve health, and make a positive, daily impact in our communities
As a Sr. Data Engineer, you will prepare and transform data for analytical, operational, and intelligent automation uses to support diverse stakeholder needs throughout the Center for International of Blood and Marrow Transplant Research (CIBMTR) , including statisticians, data scientists, scientific directors, and CIBMTR partners. Design, develop, and implement data- and AI-centric solutions aligned with evolving user needs-leveraging structured and unstructured data, optimizing data quality, and enabling scalable Machine Learning and Agentic Artificial Intelligence (AI) systems. Responsibilities:
- Lead or actively contribute to multidisciplinary data and AI workstreams, collaborating with data scientists, analytics engineers, and partner engineering teams to design and build next-generation intelligent data solutions.
- Design and implement modern, scalable, secure, high performing data architectures, including data lakes, lakehouse and data commons.
- Develop and optimize data pipelines (ETL/ELT) and orchestration systems for large scale data ingestion and processing of structured and unstructured data as well as integrating organizational data for ML/AI workloads for analytics and ML/AI applications.
- Build reusable, modular components and APIs to support scalable Agentic AI frameworks and enable autonomous data operations aligned with outcomes research and clinical trials.
- Work independently or as part of a team with subject matter experts to identify user needs and requirements for efficient, scalable and reliable data pipelines and models that support data-driven initiatives.
- Support automation of operational workflows using Agentic AI, including evaluation, performance tuning and observability.
- Develop and maintain clear documentation aligned with Standard Operating Procedures (SOPs), best practices, and regulatory requirements for both data engineering and AI components.
- Mentor and train data engineers and analytics engineers in the adoption and integration of AI and ML methods and frameworks.
- Perform other duties as required.
Knowledge - Skills - Abilities
- Experience in designing, implementing, and scaling data pipelines for structured and unstructured data in modern Lakehouse or data lake architectures.
- Strong proficiency in SQL and at least one scripting language (e.g., Python).
- Solid understanding of data engineering principles, including data preparation, feature engineering, and model lifecycle management.
- Solid understanding of prompt engineering.
- Experience with cloud-based AI/ML platforms (e.g., AWS SageMaker, Bedrock, or comparable).
- Familiarity with LLMs, agentic frameworks, and AI orchestration patterns (e.g., LangChain, AutoGen, or similar).
- Familiarity with techniques to integrate organizational data into AI workflows, such as Retrieval Augmented Generation (RAG).
- Strong data profiling and data quality assurance experience.
- Knowledge of workflow decomposition for automation.
- Excellent problem-solving, analytical thinking, and communication skills.
- Ability to mentor technical staff and communicate data engineering and AI concepts to non-expert audiences.
Preferred:
- Knowledge of data interoperability and data standards (e.g., FHIR, HL7, JSON, XML).
- Experience with Agentic AI reasoning patterns and system frameworks.
- Experience working in AGILE Scrum team framework.
- Familiarity with orchestration tools (e.g. Airflow or Dagster).
- Familiarity of R, SAS, JupytrLab or other statistical software is a plus.
- Experience with Model Context Protocol (MCP), RESTful APIs and modern integration methods.
- Familiarity of model evaluation and observability.
Preferred Schedule:
Mon-Friday
Position Requirements:
Minimum Qualifications: Appropriate experience may be substituted for education on an equivalent basis. Minimum education: Bachelor's Degree Minimum experience: 5 years Preferred Qualifications: Preferred education: Master's degree Preferred experience: 8 years in Computer Science, Informatics, Data Science, or technical discipline in healthcare or life sciences. AI/ML certifications are preferred. Why MCW?
- Outstanding Healthcare Coverage, including but not limited to Health, Vision, and Dental.
- 403B Retirement Package
- Competitive Vacation, Sick Time, and Paid Holidays
- Tuition Reimbursement
- Paid Parental Leave
For a brief overview of our benefits see: https://www.mcw.edu/departments/human-resources/benefits #LI-NK1
MCW as an Equal Opportunity Employer and Commitment to Non-Discrimination
The Medical College of Wisconsin (MCW) is an Equal Opportunity Employer. We are committed to fostering an inclusive community of outstanding faculty, staff, and students, as well as ensuring equal educational opportunity, employment, and access to services, programs, and activities, without regard to an individual's race, color, national origin, religion, age, disability, sex, gender identity/expression, sexual orientation, marital status, pregnancy, predisposing genetic characteristic, or military status. Employees, students, applicants, or other members of the MCW community (including but not limited to vendors, visitors, and guests) may not be subjected to harassment that is prohibited by law or treated adversely or retaliated against based upon a protected characteristic.
.
|