{"schemaVersion":"jobsearcher.job.v1","id":"08e7af66917e19b094b92072","url":"https://jobsearcher.com/jobs/08e7af66917e19b094b92072","canonicalUrl":"https://jobsearcher.com/jobs/08e7af66917e19b094b92072","title":"RevOps Analytics Engineer","description":"Position Overview\n\nLean Layer is the #1 Rated RevOps Agency on G2, and we’re doubling our consulting team over the next year. Our reputation is built on excellent results, which means we need to keep hiring excellent people. We are looking for a RevOps Analytics Engineer with deep Revenue Operations expertise to own and maintain the data infrastructure that powers revenue analytics and reporting across our client environments.\n\nThis role focuses on data engineering and warehouse management, ensuring reliable pipelines, scalable data models, and high-quality revenue data. The RevOps Analytics Engineer will work closely with RevOps consultants who define CRM and business requirements, and with data analysts who build dashboards and reporting.\n\nYou may be a fit for the RevOps Analytics Engineer role if you are strong in SQL, data modeling, and warehouse architecture, and can understand the business context of revenue operations in order to build reliable and scalable data systems.\n\nWhat We’re Looking For\n\nThe ideal candidate:\n\nEnjoys building reliable data systems and solving complex data problems\n\nHas strong technical data engineering skills\n\nUnderstands how revenue teams use data for reporting and decision-making\n\nCan translate business context into scalable data models\n\nIs comfortable working across multiple systems and client environments\n\nIs comfortable working directly with clients as needed\n\nThrives in collaborative, fast-paced environments\n\nKey Responsibilities\n\nData Warehouse Ownership:\n\nDesign and maintain datasets and table structures\n\nManage warehouse performance, partitioning, clustering, and cost optimization\n\nMaintain access controls and permissions\n\nStructure warehouse schemas to support revenue analytics and reporting\n\nData Pipelines & Integrations:\n\nBuild and maintain ETL / ELT pipelines from revenue systems into the warehouse\n\nIntegrate data from systems such as HubSpot, Salesforce, marketing and sales analytics platforms, sales engagement platforms, billing systems, and product analytics tools\n\nMonitor pipeline health and resolve failures\n\nManage schema changes from upstream systems\n\nEnsure reliable and timely data synchronization\n\nManage GitHub repositories\n\nData Modeling for Revenue Analytics:\n\nDesign and maintain analytics-ready data models\n\nBuild models for accounts, contacts, opportunities, and pipeline data\n\nBI & Analytics Support:\n\nMaintain tables and models used by BI tools such as Looker\n\nOptimize queries and support derived tables used in reporting\n\nEnsure consistent metric definitions across reporting layers\n\nDashboard creation for data validation\n\nData Quality & Reliability:\n\nImplement data validation and testing\n\nMonitor pipeline health and data freshness\n\nIdentify and resolve data inconsistencies\n\nMaintain documentation for warehouse models and data definitions\n\nRequired Qualifications\n\n3–5 years of experience in data engineering or analytics engineering\n\nStrong SQL skills\n\nExperience working with data warehouses (BigQuery, Snowflake, Redshift, etc.)\n\nExperience working with Salesforce or HubSpot as a data source\n\nExperience building and maintaining ETL / ELT pipelines\n\nExperience designing analytics-ready data models\n\nFamiliarity with API-based integrations and data syncing\n\nPython for data pipelines or automation\n\nReverse ETL or operational data workflows\n\ndbt or similar transformation tools\n\nLooker or similar BI platforms\n\nExperience with GitHub\n\nPreferred Experience\n\nExperience working with revenue or business systems and terminology such as:\n\nMarketing Automation Platforms (MAP) like HubSpot\n\nMarketing analytics platforms\n\nSaaS revenue metrics (ARR, ACV, TCV, MRR, etc.)\n\nSaaS terminology (MQL, SQL, SQO, Deal/Opportunity, Lead/Contact, etc.)\n\nLearn more about what it's like to work at Lean Layer here.\n\nVisa Sponsorship: Please note that we are not currently able to offer U.S. visa sponsorship or transfer for this position.\n\nFor Canadian and Brazilian Residents: We also invite you to apply for this position but please note that at this time we can only hire those outside of the United States as full-time contractors. If you have any questions about this set up, please don't hesitate to reach out.\n\nCompensation Range: $40K - $165K","company":"Lean Layer","rawCompany":"lean layer","city":"New York","state":"NY","isRemote":false,"isActive":false,"createdAt":"2026-09-04T09:16:46.393Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"RevOps Analytics Engineer","description":"Position Overview\n\nLean Layer is the #1 Rated RevOps Agency on G2, and we’re doubling our consulting team over the next year. Our reputation is built on excellent results, which means we need to keep hiring excellent people. We are looking for a RevOps Analytics Engineer with deep Revenue Operations expertise to own and maintain the data infrastructure that powers revenue analytics and reporting across our client environments.\n\nThis role focuses on data engineering and warehouse management, ensuring reliable pipelines, scalable data models, and high-quality revenue data. The RevOps Analytics Engineer will work closely with RevOps consultants who define CRM and business requirements, and with data analysts who build dashboards and reporting.\n\nYou may be a fit for the RevOps Analytics Engineer role if you are strong in SQL, data modeling, and warehouse architecture, and can understand the business context of revenue operations in order to build reliable and scalable data systems.\n\nWhat We’re Looking For\n\nThe ideal candidate:\n\nEnjoys building reliable data systems and solving complex data problems\n\nHas strong technical data engineering skills\n\nUnderstands how revenue teams use data for reporting and decision-making\n\nCan translate business context into scalable data models\n\nIs comfortable working across multiple systems and client environments\n\nIs comfortable working directly with clients as needed\n\nThrives in collaborative, fast-paced environments\n\nKey Responsibilities\n\nData Warehouse Ownership:\n\nDesign and maintain datasets and table structures\n\nManage warehouse performance, partitioning, clustering, and cost optimization\n\nMaintain access controls and permissions\n\nStructure warehouse schemas to support revenue analytics and reporting\n\nData Pipelines & Integrations:\n\nBuild and maintain ETL / ELT pipelines from revenue systems into the warehouse\n\nIntegrate data from systems such as HubSpot, Salesforce, marketing and sales analytics platforms, sales engagement platforms, billing systems, and product analytics tools\n\nMonitor pipeline health and resolve failures\n\nManage schema changes from upstream systems\n\nEnsure reliable and timely data synchronization\n\nManage GitHub repositories\n\nData Modeling for Revenue Analytics:\n\nDesign and maintain analytics-ready data models\n\nBuild models for accounts, contacts, opportunities, and pipeline data\n\nBI & Analytics Support:\n\nMaintain tables and models used by BI tools such as Looker\n\nOptimize queries and support derived tables used in reporting\n\nEnsure consistent metric definitions across reporting layers\n\nDashboard creation for data validation\n\nData Quality & Reliability:\n\nImplement data validation and testing\n\nMonitor pipeline health and data freshness\n\nIdentify and resolve data inconsistencies\n\nMaintain documentation for warehouse models and data definitions\n\nRequired Qualifications\n\n3–5 years of experience in data engineering or analytics engineering\n\nStrong SQL skills\n\nExperience working with data warehouses (BigQuery, Snowflake, Redshift, etc.)\n\nExperience working with Salesforce or HubSpot as a data source\n\nExperience building and maintaining ETL / ELT pipelines\n\nExperience designing analytics-ready data models\n\nFamiliarity with API-based integrations and data syncing\n\nPython for data pipelines or automation\n\nReverse ETL or operational data workflows\n\ndbt or similar transformation tools\n\nLooker or similar BI platforms\n\nExperience with GitHub\n\nPreferred Experience\n\nExperience working with revenue or business systems and terminology such as:\n\nMarketing Automation Platforms (MAP) like HubSpot\n\nMarketing analytics platforms\n\nSaaS revenue metrics (ARR, ACV, TCV, MRR, etc.)\n\nSaaS terminology (MQL, SQL, SQO, Deal/Opportunity, Lead/Contact, etc.)\n\nLearn more about what it's like to work at Lean Layer here.\n\nVisa Sponsorship: Please note that we are not currently able to offer U.S. visa sponsorship or transfer for this position.\n\nFor Canadian and Brazilian Residents: We also invite you to apply for this position but please note that at this time we can only hire those outside of the United States as full-time contractors. If you have any questions about this set up, please don't hesitate to reach out.\n\nCompensation Range: $40K - $165K","datePosted":"2026-09-04T09:16:46.393Z","dateModified":"2026-09-04T09:16:46.393Z","hiringOrganization":{"@type":"Organization","name":"Lean Layer","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York","addressRegion":"NY","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"08e7af66917e19b094b92072"},"url":"https://jobsearcher.com/jobs/08e7af66917e19b094b92072"}}