[Hiring] RevOps Analytics Engineer @Lean Layer

Role Description

Lean 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
• Understanding the business context of revenue operations to build reliable and scalable data systems

Qualifications

• 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

Requirements

• Enjoys building reliable data systems and solving complex data problems
• Has strong technical data engineering skills
• Understands how revenue teams use data for reporting and decision-making
• Can translate business context into scalable data models
• Is comfortable working across multiple systems and client environments
• Is comfortable working directly with clients as needed
• Thrives in collaborative, fast-paced environments

Key Responsibilities

• Data Warehouse Ownership:
  • 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
• Data Pipelines & Integrations:
  • 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
• Data Modeling for Revenue Analytics:
  • Design and maintain analytics-ready data models
  • Build models for accounts, contacts, opportunities, and pipeline data
• BI & Analytics Support:
  • 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
• Data Quality & Reliability:
  • Implement data validation and testing
  • Monitor pipeline health and data freshness
  • Identify and resolve data inconsistencies
  • Maintain documentation for warehouse models and data definitions

Benefits

• This role is open to candidates based in Brazil only and is a contract-to-hire opportunity.
• You’ll start on an hourly contract, with up to 40 hours of work per week.
• The salary listed reflects the full-time compensation for the role, and we’ll set your hourly rate based on your full-time expectations.