Job Title: RevOps Analytics Engineer

Company Name: Lean Layer

Job Details: $40k-$120k/yrRemoteFull,Time

Job Url: https://hiring.cafe/viewjob/cqp3wlddgy3zp8lx

Job Description: Posted 5d agoRevOps Analytics Engineer@ Lean LayerView All JobsWebsiteNew York, New York, United States$40k-$120k/yrRemoteFull TimeResponsibilities:Own warehouse, Build pipelines, Model dataRequirements Summary:3-5 years data engineering/analytics engineering; strong SQL; data warehousing experience; ETL/ELT pipelines; data modeling; API integrations; Python; reverse ETL; dbt; Looker; GitHub.Technical Tools Mentioned:SQL, BigQuery, Snowflake, Redshift, Salesforce, HubSpot, ETL/ELT, Python, dbt, Looker, GitHub
Position OverviewLean 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.This 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.You 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.What We’re Looking ForThe ideal candidate:Enjoys building reliable data systems and solving complex data problemsHas strong technical data engineering skillsUnderstands how revenue teams use data for reporting and decision-makingCan translate business context into scalable data modelsIs comfortable working across multiple systems and client environmentsIs comfortable working directly with clients as neededThrives in collaborative, fast-paced environmentsKey ResponsibilitiesData Warehouse Ownership:Design and maintain datasets and table structuresManage warehouse performance, partitioning, clustering, and cost optimizationMaintain access controls and permissionsStructure warehouse schemas to support revenue analytics and reportingData Pipelines & Integrations:Build and maintain ETL / ELT pipelines from revenue systems into the warehouseIntegrate data from systems such as HubSpot, Salesforce, marketing and sales analytics platforms, sales engagement platforms, billing systems, and product analytics toolsMonitor pipeline health and resolve failuresManage schema changes from upstream systemsEnsure reliable and timely data synchronizationManage GitHub repositoriesData Modeling for Revenue Analytics:Design and maintain analytics-ready data modelsBuild models for accounts, contacts, opportunities, and pipeline dataBI & Analytics Support:Maintain tables and models used by BI tools such as LookerOptimize queries and support derived tables used in reportingEnsure consistent metric definitions across reporting layersDashboard creation for data validationData Quality & Reliability:Implement data validation and testingMonitor pipeline health and data freshnessIdentify and resolve data inconsistenciesMaintain documentation for warehouse models and data definitionsRequired Qualifications3–5 years of experience in data engineering or analytics engineeringStrong SQL skillsExperience working with data warehouses (BigQuery, Snowflake, Redshift, etc.)Experience working with Salesforce or HubSpot as a data sourceExperience building and maintaining ETL / ELT pipelinesExperience designing analytics-ready data modelsFamiliarity with API-based integrations and data syncingPython for data pipelines or automationReverse ETL or operational data workflowsdbt or similar transformation toolsLooker or similar BI platformsExperience with GitHubPreferred ExperienceExperience working with revenue or business systems and terminology such as:Marketing Automation Platforms (MAP) like HubSpotMarketing analytics platformsSaaS revenue metrics (ARR, ACV, TCV, MRR, etc.)SaaS terminology (MQL, SQL, SQO, Deal/Opportunity, Lead/Contact, etc.)Learn more about what it's like to work at Lean Layer here. Visa Sponsorship: Please note that we are not currently able to offer U.S. visa sponsorship or transfer for this position. For Canadian 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 to.