AI Engineer - Mid-Level

As a Data Engineer II on the Data & Analytics team at St.

Peter’s Health, you’ll play a key role in building and supporting the data solutions that help drive better healthcare decisions.

You’ll design and maintain data pipelines, integrations, models, and cloud-based data assets while working with clinical, financial, operational, and business teams to turn complex data into trusted, actionable insights.

Using technologies such as SQL and Snowflake, you’ll help modernize our data environment, improve data quality and reliability, and support secure, governed access to information across the organization.

This role offers the opportunity to work independently, collaborate with a talented team, explore responsible AI-enabled tools, and make a meaningful impact through data.

• Four or more years of relevant experience in data engineering, data analytics, database development, business intelligence, or related information technology work; or an equivalent combination of education and experience.
• Strong working knowledge of SQL and relational database concepts.
• Experience independently designing and supporting data extracts, data transformations, data validation, reporting datasets, analytical data assets, and production data pipelines.
• Working knowledge of data modeling, data quality, data integration, orchestration, monitoring, and production support concepts.
• Demonstrated ability to document technical work clearly, including data mappings, business rules, process steps, runbooks, and support procedures.
• Demonstrated analytical, written, verbal, customer service, and stakeholder engagement skills.

• Healthcare provider, payer, health system, or healthcare analytics experience.
• Experience with Epic, Clarity, Caboodle, Cogito, or a comparable EHR system.
• Experience with Snowflake or a comparable cloud data platform; BI tools; ETL/ELT or orchestration tools.
• Experience with Git, Azure DevOps, APIs, SFTP, or file-based data exchange patterns.
• Experience with Python, dbt, AWS Glue, Azure Data Factory, or similar data engineering tools.
• Familiarity with HIPAA, HITECH, healthcare data privacy, information security practices, and responsible use of AI-enabled productivity tools.

Bachelor’s degree in Computer Science, Computer Information Systems, Data Analytics, Health Informatics, Engineering, Mathematics, Statistics, Business Analytics, or a related field is preferred.

In the absence of a bachelor’s degree, an associate degree or relevant advanced certifications in a related field with six or more years of relevant experience may be accepted.

A master’s degree in a related field is preferred and may substitute for a portion of required experience.

Equivalent combinations of education, certification, and directly relevant experience may be considered.

LICENSE/CERTIFICATION/REGISTRY: No license required.

Preferred certifications include Snowflake, Epic Cogito/Clarity/Caboodle, Microsoft Azure, AWS, SQL, data engineering, data analytics, cloud data platform, information security, or healthcare analytics credentials.