AI Data Engineer

InterMed, P.A.•South Portland, ME

2d•$105,373 - $152,880

About The Position

The AI Data Engineer is a hands-on technical expert responsible for building InterMed’s data foundation and AI-driven applications to automate work and improve decision-making. The role develops custom applications and AI agents that automate business and clinical workflows, leverages EMR and other healthcare data, and helps the Business Intelligence (BI) team develop its Python and AI-assisted development capabilities. The position builds and optimizes InterMed’s cloud data platform using Microsoft Fabric and Power BI, including semantic models that support AI-assisted reporting and self-service. It also supports the existing SQL environment as workloads transition to Fabric. The ideal candidate combines strong data engineering fundamentals with hands-on experience in LLM and AI tools and an interest in applying AI to reshape data strategy. The role includes migrating BI workloads from on-premises SQL and SSIS to Fabric; building and maintaining data pipelines, warehouse models, semantic models, Python automation, and APIs; and ensuring data quality, integrity, security, and HIPAA/PHI safeguards. It also evaluates and integrates LLM tooling, establishes responsible AI-assisted development practices, creates applications and agents for multi-step workflows, advises on AI vendor solutions, partners with IT on deployment and operations, and coaches analysts in Python and AI-assisted development. The employee is expected to follow InterMed’s mission and values, maintain strict confidentiality in accordance with HIPAA guidelines and InterMed policies, and perform other duties that support the organization’s mission, vision, and values.

Requirements

Bachelor’s degree in Computer Science, Information Systems, or a related field, or an equivalent combination of education and experience.
3–5 years of hands-on experience with AI, data engineering, BI development, or data architecture, including demonstrated ownership of production pipelines and infrastructure.
Proficiency in Python for data engineering, including transformation, automation, pipeline development, and data quality scripts.
Advanced SQL skills and strong data modeling expertise, including dimensional modeling, star schema design, and performance optimization; hands-on experience in SQL Server environments.
Hands-on, daily experience using AI coding assistants and AI tools to write, test, debug, and document code and queries, with judgment to review generated output and understand AI limitations.
Experience designing Power BI semantic models, including relationships, governed measures, and descriptions that support accurate AI-generated reports and answers.
Deep knowledge of modern data architecture patterns, such as lakehouse, medallion, or cloud ELT, and the ability to plan migration from legacy on-premises environments.
Hands-on experience with a SQL-based transformation framework and a pipeline orchestration tool.
Experience building applications or AI agents that automate multi-step workflows using low-code platforms and/or Python with LLM APIs and agent frameworks.
Ability to work with unstructured and semi-structured data, such as clinical notes, documents, and JSON, in addition to relational data.
Ability to coach analysts with varied technical backgrounds and raise team coding standards.
Strong analytical reasoning and problem-solving skills, including the ability to work effectively in ambiguous environments and lead through uncertainty.
Clear communication skills, including the ability to explain technical concepts, architecture tradeoffs, and migration plans to non-technical audiences and leadership.
Deep understanding of data engineering, analytics, and end-to-end data workflows from source system to consumption layer.
Demonstrated experience delivering at least one production application, automation, or AI agent that replaced a manual business process.
Experience with version control, CI/CD workflows, and code review practices for data assets.
Demonstrated ability to design, document, and govern enterprise data models and architecture.
Maintain confidentiality in accordance with HIPAA guidelines and InterMed policies.

Nice To Haves

Familiarity with Microsoft Fabric and Power BI and how they fit within the broader Microsoft environment, including Azure, M365, and Microsoft Entra ID.
Experience in healthcare, health tech, or regulated environments; familiarity with HIPAA/PHI is a plus.
Familiarity with Microsoft Fabric, Azure data services, Snowflake, or a comparable cloud data platform and its integration within the broader Microsoft technology environment.
Hands-on experience with SQL Server and SSMS-based environments is preferred.

Responsibilities

Assist with migrating BI workloads from on-premises SQL and SSIS to Microsoft Fabric; assess legacy packages for retirement, rebuilding, or re-architecture, and maintain existing SQL Server, SSMS workflows, and SSIS packages during the transition.
Design and build data pipelines into Fabric OneLake from source systems, including orchestration, scheduling, dependency management, alerting, and failure recovery.
Complete data warehouse development across priority subject areas using a SQL-based transformation framework for modular, tested, version-controlled, and documented models.
Build and publish certified Power BI semantic models with governed measures, definitions, and business-friendly descriptions for Copilot report building and self-service data agents; support transition from Tableau to Power BI.
Build and maintain Python automation scripts and APIs for data pipelines, applications, and agents.
Ensure data quality, integrity, and security across the platform, including HIPAA and PHI safeguards and automated monitoring and alerting on key data quality metrics.
Evaluate and integrate LLM-powered tools to accelerate data workflows and enable natural-language data access.
Establish standards for responsible AI-assisted development, including AI-supported code and query writing, review, testing, and documentation, with human review of generated output.
Use AI to optimize dashboards and end-user agent and self-service analytics capabilities.
Design, build, and deploy purpose-built applications and AI agents that automate BI, IT, administrative, and clinical workflows from data intake through action and audit trail.
Develop applications and agents using Microsoft low-code tools and Python- and LLM-based custom agents for multi-step workflows that low-code tools do not adequately address.
Leverage EMR and other structured and unstructured data sources to support analytics, automation, and clinical and operational use cases while complying with HIPAA and PHI safeguards.
Partner with IT on application and agent integration, deployment, and ongoing operation.
Advise IT and business partners on AI vendor point solutions, including fit, overlap with in-house capabilities, data access and integration requirements, and build-versus-buy tradeoffs.
Develop analyst capability in Python, flexible coding, unstructured data techniques, and AI-assisted development through coaching, code review, shared patterns, and templates.
Maintain strict confidentiality in alignment with HIPAA guidelines and InterMed policies.
Perform other duties in support of InterMed’s mission, vision, and values.
Follow InterMed’s patient-centered mission and values, including providing high-quality service, treating patients and colleagues with dignity and respect, acting with honesty and integrity, emphasizing teamwork and accountability, and embracing change.