About this role
8+ years of experience in Data Engineering, Analytics Engineering, or related fields.3+ years of hands-on experience with dbt in production environments.Strong expertise in SQL and complex data transformation development.Strong understanding of dbt Core and/or dbt Cloud.Experience with dbt models and materializationExperience with incremental models Experience building and maintaining macros using JinjaExperience with dbt tests and data quality frameworksExperience with snapshotsExperience with seeds and sources Experience with documentation and data lineageExperience using dbt packagesStrong experience with at least one cloud data platform: SnowflakeDatabricksGoogle BigQueryAmazon RedshiftDaily, fluent use of Claude Code and/or GitHub Copilot for implementation, refactoring, test generation, and code reviewAbility to establish team standards for AI-assisted development: effective prompting, trust-vs-verify discipline on generated code, security/IP guardrails, and reviewing AI-authored changesWorking understanding of LLM fundamentals: context windows, tokens, model selection, and prompt/context engineeringExperience integrating AI into developer workflows and agentic/automation tooling (MCP servers, AI-driven CI steps, codegen and doc-generation pipelines)Able to evaluate AI tooling pragmatically: measuring real productivity and quality impact, not hype