Solutions Engineer (AI)

Bachelor’s degree in Healthcare Informatics, Data Science, Computer Science, Information Systems, Business Analytics, or related field. 4–7 years of experience in data integration, analytics, or technical solution delivery. Proven experience with healthcare data or CRM-based programs. 5+ years of experience supporting healthcare or life sciences data integrations. Experience working with AI-powered analytics or predictive modeling tools. Demonstrated success in pre-sales or solution design roles. Familiarity with ETL/ELT processes, dbt, or modern data stack tools. Experience delivering cloud-based analytics in a multi-tenant SaaS environment. Advanced SQL skills. Hands-on experience with data warehouse environments (Snowflake, MS SQL Server). Understanding of data modeling, normalization, and CRM architectures (Salesforce, Veeva, HubSpot). Proven ability to document and communicate data transformation logic. Python or scripting for automation and data manipulation. API data structures (JSON/XML). Familiarity with AI/ML data pipelines or feature engineering. Skilled at leading technical discussions and translating complex data concepts. Comfortable collaborating with executive stakeholders and data engineers. Strong written and verbal communication skills.

Lead technical discovery sessions with clients to assess workflows, CRM data, and backend data systems. Develop and execute SQL queries and BI reports to explore, validate, and reconcile client data. Design and document data mapping between client objects and internal data models. Translate client business requirements into actionable technical specifications. Review and validate code outputs and workflow logic. Produce technical and client-facing documentation. Provide quality assurance (QA/QC) oversight for data transformations. Partner with Account Management and Engineering on post-implementation success. Support pre-sales and solution scoping activities.