Data Engineer

• Design, build, and maintain data ingestion pipelines feeding SmartLight’s Snowflake warehouse from claims, eligibility, and other healthcare data sources
• Develop and maintain transformation models in dbt, following testing, documentation, and version-control best practices
• Contribute to fact and dimensional modeling (star schema design, slowly changing dimensions, grain definition) supporting claims analytics use cases
• Support and help maintain a semantic layer that gives consistent, governed metrics to downstream reporting tools (e.g., Sigma)
• Troubleshoot data quality issues, pipeline failures, and schema drift with minimal escalation
• Write idempotent, reliable pipeline logic that can be safely rerun without creating duplicate or inconsistent data
• Collaborate with senior data engineers, analysts, and product stakeholders to translate business/reporting requirements into technical data structures
• Use AI-assisted development tools (Claude, Copilot, or similar) as a core part of your daily workflow - for code generation, debugging, documentation, and accelerating pipeline development - while maintaining human review and code quality standards
• Follow SmartLight’s change management, SDLC, and data security practices, given the sensitivity of the healthcare data we handle, * You can take a data ingestion or modeling task, ask clarifying questions up front, and deliver a working, tested solution without needing hand-holding through implementation
• Your dbt models are well-documented, tested, and follow the team’s established modeling conventions
• You proactively flag data quality issues or schema risks before they become downstream reporting problems
• You use AI tools fluently to move faster without sacrificing code quality, security, or accuracy - especially given SmartLight’s obligations around GenAI use disclosure in some client contracts
• You grow into increasing ownership of the Snowflake buildout over time, with a path toward more senior data engineering responsibilities

• Solid foundational knowledge of data engineering: ETL/ELT concepts, SQL proficiency, and data pipeline design
• Working knowledge of dbt (or strong readiness to ramp quickly if exposure is limited) for transformation and modeling
• Understanding of fact and dimensional modeling principles (star/snowflake schemas, grain, SCDs)
• Familiarity with the concept of a semantic layer and why it matters for consistent, trustworthy reporting
• Strong data translation fundamentals - the ability to take a business question or reporting requirement and reason through the correct data structure/logic to answer it accurately
• Ability to work independently and complete assigned tasks with minimal day-to-day supervision once requirements are clear
• Comfort using AI tools as a core part of the development process - this is a non-negotiable expectation of how we build, not an optional add-on
• Strong written communication skills for documentation and cross-team collaboration

Preferred:

• Prior experience in healthcare data (claims, eligibility, EHR, or similar) - familiarity with concepts like UB-04 revenue codes, claims adjudication, or payer/provider data structures is a plus
• Experience with Snowflake specifically
• Exposure to Terraform or other infrastructure-as-code practices
• Familiarity with Sigma, Looker, Power BI, or other modern BI/reporting tools
• Understanding of HIPAA-related data handling considerations

SmartLight is building out its next-generation Snowflake data warehouse to power claims analytics, waste and abuse analytics, and client reporting at scale. We’re looking for a Junior Data Engineer to join our Data Platform Team and grow alongside a modern, AI-augmented data stack. This is a hands-on role: you’ll ingest and model real healthcare claims data, build transformation pipelines in dbt, and help shape the fact/dimensional models and semantic layer that our analysts and reporting tools depend on every day.