> Markdown version of [/jobs/ext/3644729-lead-data-analytics-engineer](https://www.wearedevelopers.com/jobs/ext/3644729-lead-data-analytics-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Analytics Engineer - **Company:** Insight Global - **Location:** Wheat Ridge, CO, United States - **Experience:** Expert - **Salary:** $135,200.0 - $156,000.0 - **Contract:** Temporary contract - **Skills:** Clean Code Principles, Query Performance, Automation of Tests, Business Intelligence Development, Continuous Integration, Information Engineering, Dimensional Modeling, Github, Query Optimization, SQL Databases, Snowflake, Agentic-AI, Data Analytics, Star Schema - **Published:** October 9, 2026 - **Apply:** https://www.disabledperson.com/jobs/75920364-lead-data-analytics-engineer ## About the Role * Six or more years in analytics engineering, data engineering, or BI development, including time working at a senior or lead level. * Production Snowflake experience, including query performance tuning, data quality aspects, and cost-aware design * Production dbt experience integrated with Snowflake and version-controlled in GitHub: model structure, tests, macros, and generated documentation * Working command of GitHub-based CI/CD - branching strategy, pull request review, automated test execution on merge, and release * Expert SQL, with command of best practices: readable and maintainable code, and query optimization * Star schema dimensional modeling, including grain definition, conformed dimensions, and handling history (SCD Type 2) * Experience building within a medallion architecture, or a directly comparable layered pattern * Experience building or maintaining a semantic layer with consistent measure definitions for downstream reporting * Hands-on experience with AI agents applied in a data or analytics context * Delivery experience in an agile environment, working to sprint commitments and taking part in planning, review, and retrospective * Experience in a productized data environment, where data sets and reports are maintained as durable products with named owners and consumers, rather than delivered as one-off requests