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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Analytics Engineer - **Company:** Netbrain - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $160,000.0 - $190,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, BigQuery, Information Engineering, Data Security, Data Warehousing, Python (Programming Language), Machine Learning, Operational Databases, Raw Data, Standard Sql, Salesforce.Com, Tableau (Software), Scripting, Large Language Models, Snowflake, Hubspot, Looker Analytics, Data Pipelines - **Published:** September 17, 2026 - **Apply:** https://www.builtincolorado.com/job/data-analytics-engineer/11215093?handler=ApplyRedirect ## About the Role * 6+ years in analytics engineering, data engineering, or a similar role, with real ownership of production data models. * Strong SQL and a track record shipping analytical models that other teams depend on. * Hands-on experience with a modern cloud data warehouse (Snowflake preferred, or comparable platforms like BigQuery). * Extensive experience with a transformation framework such as dbt or SQLMesh. * Scripting ability (Python or similar) for ingestion, validation, or automation. * Experience with a BI or semantic-layer tool (e.g., Omni, Looker, Tableau). * Sound judgment around data access, governance, and handling of sensitive data. * Manual Dexterity: Repetitive motion of wrists, hands and fingers for using a computer. * Stationary Tasks: Sitting for extended periods, remaining in a stationary position. Nice to Have * Experience building the technical foundation for AI-assisted or natural-language reporting - semantic layers built to support LLM or agent-based tools. * Familiarity with GTM and Customer Success data sources such as Salesforce, Gainsight, or HubSpot. * Experience applying machine learning or statistical forecasting techniques (e.g., time-series and churn-propensity models) to predict key business metrics such as ARR and customer retention. ## Description Architect and maintain NetBrain's first cloud data warehouse, ELT pipelines, transformation layer, semantic models, and BI foundation. Own data quality, governance, lineage, access controls, and curated models supporting product usage, customer adoption, account health, and go-to-market reporting. Partner with stakeholders to establish reliable metrics and a standardized source of truth, while supporting AI-assisted analytics and natural-language reporting use cases., NetBrain doesn't have a data warehouse today - different teams work from different numbers, with no standardized reporting layer or single source of truth for the business. We're hiring a Senior Analytics Engineer to fix that: architecting and standing up our first cloud data warehouse, and building the transformation layer, ELT pipelines, and governance that our analytics function will run on. You'll own the technical infrastructure that makes reliable measurement possible - warehouse, pipelines, and transformations - while partnering closely with the business stakeholders who define what we measure and why. This is a foundational build with high visibility: the semantic layer you help stand up is also core to how NetBrain uses AI internally to query and report on its own data. What You'll Do * Architect and maintain NetBrain's cloud data warehouse, * Own warehouse transformations end to end - from raw ingestion through documented, stable tables that downstream teams and tools depend on. * Design and maintain ELT pipelines that bring raw data from tools across GTM, Finance, and Product into the warehouse. * Contribute to the technical foundation of our BI tool - semantic layer, metric definitions, and access model - that powers executive reporting and NetBrain's internal AI use cases. * Own data quality, governance, and lineage: freshness checks, testing, access controls, and a documented source of truth. * Build and maintain curated data models for product usage, customer adoption, account health, and go-to-market reporting. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Integrate your Cognitive Assistant with 3rd-party DBs and software](https://www.wearedevelopers.com/videos/249-integrate-your-cognitive-assistant-with-3rd-party-dbs-and-software) - [Making Data Warehouses fast. 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