Data and AI Solutions Engineer

SUMMARY DESCRIPTION

Under the direction of the Digital Intelligence Manager, the Data & AI Solutions Engineer should be a versatile and forward‑thinking professional to help modernize and use data. The Data & AI Solutions Engineer will participate in the development and maintenance of the SIA data lake, delivering actionable insights through dashboards and reports, supporting the next generation claims system, and implementing automation and AI solutions across the organization.

• Assist with Data Lake Development & Maintenance:
  Design, build, and maintain the data lake environment; implement medallion architecture (Bronze/Silver/Gold layers) for claims, finance, and risk datasets; establish governance, quality checks, and documentation for ingested data.
• Assist with Data Integration and Extract, Transform, Load (ETL):
  Build and manage robust ELT pipelines for multiple internal and external data sources (claims systems, finance, risk management, prevention services); automate data refresh processes and ensure accuracy, timeliness, and security.
• Support Business Intelligence Reporting and Analytics:
  Develop dashboards, reports, and other BI delivery methods using Power BI and/or other selected tools or custom programming, tailored for departmental and executive stakeholders; assist claim, finance, risk, prevention, and IT leadership to deliver insights on claims trends, costs, prevention activities, and other performance metrics; train and support staff in using reports, dashboards, and other self‑service BI tools.
• Claims System Support:
  Collaborate with IT and vendors to support and enhance the next generation claims system; assist with data migrations, integrations, and system testing; troubleshoot and resolve system/data issues in partnership with IT and business units.
• Support AI and Automation Improvement Efforts:
  Identify opportunities for AI‑driven tools (e.g., document intelligence, natural language dashboards, claims triage support); build and deploy AI/automation solutions that improve efficiency, reduce risk, and support compliance; support governance and responsible AI use in alignment with organizational policies.
• Custom Applications and Scripting:
  Design, build, and maintain custom in‑house applications, scripts, and automation to support business practices (e.g., claims workflows, data exports, system monitoring, IT automation); manage source control, versioning, and documentation of scripts/tools; work with staff to identify opportunities where lightweight applications or scripts can fill operational gaps quickly and effectively; participate in special projects as needed; perform related duties as needed.

Hands‑on experience with data engineering and ETL (SQL, Python, or comparable); proficiency in Microsoft 365 applications; proficiency in Power BI and familiarity with Microsoft Fabric/Azure data services preferred; strong knowledge of relational databases (SQL Server preferred); experience building and supporting reporting and dashboards for senior stakeholders preferred; ability to translate business needs into technical solutions; a builder’s mindset – enjoys creating new systems and solutions;

excellent communicator, able to bridge technical and non‑technical audiences; self‑starter who thrives in a collaborative environment; committed to continuous learning in data, AI, and automation; familiarity with AI/ML frameworks or LLM‑based automation preferred; knowledge of API integrations, containerized environments (Docker), or workflow automation (Power Automate) preferred; understanding of data governance, privacy, and compliance standards (FERPA, HIPAA, CMS Section 111) preferred.

Any combination of education and experience that would likely provide the required knowledge and abilities is qualifying. A typical way to obtain the knowledge and abilities would be: a bachelor’s degree from an accredited college or university with major coursework in computer science, information systems, data analytics or related field preferred. Other certifications or experience will be considered. Three years of increasingly responsible data engineering experience.

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential job functions. Standard office setting; exposure to computer screens; sufficient physical ability to work in an office setting and operate office equipment; sit or stand for prolonged periods of time; light lifting. Vision sufficient to read computer screens and printed documents.

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