{"schemaVersion":"jobsearcher.job.v1","id":"68bdd57d92ea7aac68456c59","url":"https://jobsearcher.com/jobs/68bdd57d92ea7aac68456c59","canonicalUrl":"https://jobsearcher.com/jobs/68bdd57d92ea7aac68456c59","title":"Senior Data Engineer | Data Platform | Python | SQL | Airflow | BigQuery | Must have Startup Exp","description":"Senior Data Engineer | Data Platform | Python | SQL | Airflow | BigQuery | Must have Startup ExpSalary: $156,000 - $210,000 + competitive equityContract: PermanentStart: ASAPWorking model: Fully remote (US based)Eligibility: Must hold existing US work authorisation - no sponsorship or transfer, now or in future including F1 Visas (US residents only)Required: End-to-end data platform ownership, Python, strong SQL, pipeline orchestration, cloud data warehouse, containerised infra (Non-Negotiable)🚨 Non-Negotiables - please only apply if you have ALL of the following 🚨Core technologies:Python and strong hands-on SQL (deep enough to hold up in a live technical round)Pipeline orchestration in production (Airflow or equivalent - Prefect, Dagster)Cloud data warehouse in production (BigQuery or equivalent - Snowflake, Databricks)Containerised data infrastructure in production (Docker / Kubernetes)Built or improved CI/CD practices for data pipelinesEnvironment:Must have startup experience - you've built in a fast-moving, high-ownership environmentA blend of established mid-sized tech AND startup (leaning away from big-tech-only profiles)Owned data platform architecture end-to-end, not just implementing pipelines to specComfortable making architectural decisions independently and owning outcomes, not just executionHands-on-keyboard - still shipping code and debugging production, not whiteboard-onlyKey skills:6-9 years as a data engineer or data platform engineerOwned a broad data platform end-to-end at whole-company scope (not a single pipeline or report)Treats reliability, observability, and cost efficiency as design constraints, not afterthoughtsAble to explain complex technical concepts clearly to non-technical stakeholdersAbility to work US hoursRole OverviewWe're partnered with an established, well-funded consumer marketplace serving millions of users, and this is a rare high-ownership seat. A small, high-leverage data team owns the entire company's data platform, with genuine greenfield work up front - a major systems and revenue overhaul, plus laying the data foundations for an ambitious AI-first push.This is not a design-from-the-whiteboard role. You'll own architecture end-to-end while staying hands-on: writing pipelines, debugging production, and shipping alongside the team. What sets it apart is scope - you'll make the architectural calls independently, influence how the wider engineering org builds on the platform, and be the person others come to when a design decision needs a second opinion. Strong work-life balance and a real \"learn it all\" culture.Key ResponsibilitiesOwn and evolve data pipeline architecture across core domains - ingestion, transformation, modeling, servingLead platform-level improvements: warehouse cost management, compute efficiency, access controlSurface and lead technical initiatives (orchestration, CI/CD, developer experience) before they become blockersDrive large, complex projects spanning multiple teams, owning outcomes rather than just executionOwn monitoring and testing strategy - close observability gaps and build alerting ahead of failuresMentor other data and analytics engineers, reviewing architectural and modeling decisionsIntegrate AI meaningfully into data engineering workflows, building leverage for the whole teamNice to HaveLed a legacy ETL to modern orchestration migration end-to-endHands-on Kubernetes in productionExperience with AI-assisted tooling inside data workflowsIf you tick all of the above boxes and can start ASAP, we'd love to hear from you.","company":"Optimal","rawCompany":"optimal","city":"Denver","state":"CO","isRemote":false,"isActive":false,"createdAt":"2026-08-25T11:10:27.103Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior Data Engineer | Data Platform | Python | SQL | Airflow | BigQuery | Must have Startup Exp","description":"Senior Data Engineer | Data Platform | Python | SQL | Airflow | BigQuery | Must have Startup ExpSalary: $156,000 - $210,000 + competitive equityContract: PermanentStart: ASAPWorking model: Fully remote (US based)Eligibility: Must hold existing US work authorisation - no sponsorship or transfer, now or in future including F1 Visas (US residents only)Required: End-to-end data platform ownership, Python, strong SQL, pipeline orchestration, cloud data warehouse, containerised infra (Non-Negotiable)🚨 Non-Negotiables - please only apply if you have ALL of the following 🚨Core technologies:Python and strong hands-on SQL (deep enough to hold up in a live technical round)Pipeline orchestration in production (Airflow or equivalent - Prefect, Dagster)Cloud data warehouse in production (BigQuery or equivalent - Snowflake, Databricks)Containerised data infrastructure in production (Docker / Kubernetes)Built or improved CI/CD practices for data pipelinesEnvironment:Must have startup experience - you've built in a fast-moving, high-ownership environmentA blend of established mid-sized tech AND startup (leaning away from big-tech-only profiles)Owned data platform architecture end-to-end, not just implementing pipelines to specComfortable making architectural decisions independently and owning outcomes, not just executionHands-on-keyboard - still shipping code and debugging production, not whiteboard-onlyKey skills:6-9 years as a data engineer or data platform engineerOwned a broad data platform end-to-end at whole-company scope (not a single pipeline or report)Treats reliability, observability, and cost efficiency as design constraints, not afterthoughtsAble to explain complex technical concepts clearly to non-technical stakeholdersAbility to work US hoursRole OverviewWe're partnered with an established, well-funded consumer marketplace serving millions of users, and this is a rare high-ownership seat. A small, high-leverage data team owns the entire company's data platform, with genuine greenfield work up front - a major systems and revenue overhaul, plus laying the data foundations for an ambitious AI-first push.This is not a design-from-the-whiteboard role. You'll own architecture end-to-end while staying hands-on: writing pipelines, debugging production, and shipping alongside the team. What sets it apart is scope - you'll make the architectural calls independently, influence how the wider engineering org builds on the platform, and be the person others come to when a design decision needs a second opinion. Strong work-life balance and a real \"learn it all\" culture.Key ResponsibilitiesOwn and evolve data pipeline architecture across core domains - ingestion, transformation, modeling, servingLead platform-level improvements: warehouse cost management, compute efficiency, access controlSurface and lead technical initiatives (orchestration, CI/CD, developer experience) before they become blockersDrive large, complex projects spanning multiple teams, owning outcomes rather than just executionOwn monitoring and testing strategy - close observability gaps and build alerting ahead of failuresMentor other data and analytics engineers, reviewing architectural and modeling decisionsIntegrate AI meaningfully into data engineering workflows, building leverage for the whole teamNice to HaveLed a legacy ETL to modern orchestration migration end-to-endHands-on Kubernetes in productionExperience with AI-assisted tooling inside data workflowsIf you tick all of the above boxes and can start ASAP, we'd love to hear from you.","datePosted":"2026-08-25T11:10:27.103Z","dateModified":"2026-08-25T11:10:27.103Z","hiringOrganization":{"@type":"Organization","name":"Optimal","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Denver","addressRegion":"CO","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"68bdd57d92ea7aac68456c59"},"url":"https://jobsearcher.com/jobs/68bdd57d92ea7aac68456c59"}}