RevOps Analytics Engineer

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🕒 March 19

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Lean Layer

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2019

🤝 B2B

☁️ SaaS

B2B • SaaS

Lean Layer is a fractional RevOps, GTM, and business intelligence services firm that helps B2B companies optimize revenue technology, analytics, and go-to-market strategy. They implement and maintain CRM and RevOps infrastructure (primarily Salesforce and HubSpot), build custom revenue analytics and reporting, and help operationalize revenue strategy — acting as an extension of clients' teams to improve forecasting, conversion, and pipeline growth. Lean Layer offers fractional experts, workshops, and hands-on execution to drive measurable revenue outcomes.

📋 Description

• Design and maintain datasets and table structures • Manage warehouse performance, partitioning, clustering, and cost optimization • Maintain access controls and permissions • Structure warehouse schemas to support revenue analytics and reporting • Build and maintain ETL / ELT pipelines from revenue systems into the warehouse • Integrate data from systems such as HubSpot, Salesforce, marketing and sales analytics platforms, sales engagement platforms, billing systems, and product analytics tools • Monitor pipeline health and resolve failures • Manage schema changes from upstream systems • Ensure reliable and timely data synchronization • Manage GitHub repositories • Design and maintain analytics-ready data models • Build models for accounts, contacts, opportunities, and pipeline data • Maintain tables and models used by BI tools such as Looker • Optimize queries and support derived tables used in reporting • Ensure consistent metric definitions across reporting layers • Dashboard creation for data validation • Implement data validation and testing • Monitor pipeline health and data freshness • Identify and resolve data inconsistencies • Maintain documentation for warehouse models and data definitions

🎯 Requirements

• 3–5 years of experience in data engineering or analytics engineering • Strong SQL skills • Experience working with data warehouses (BigQuery, Snowflake, Redshift, etc.) • Experience working with Salesforce or HubSpot as a data source • Experience building and maintaining ETL / ELT pipelines • Experience designing analytics-ready data models • Familiarity with API-based integrations and data syncing • Python for data pipelines or automation • Reverse ETL or operational data workflows • dbt or similar transformation tools • Looker or similar BI platforms • Experience with GitHub

🏖️ Benefits

• Offers Commission • Offers Bonus