RevOps Analytics Engineer

Position Overview

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 , and can understand the business context of revenue operations in order to build reliable and scalable data systems.

What We’re Looking For

The ideal candidate:

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

Required 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

Preferred Experience

Experience working with revenue or business systems and terminology such as:

Marketing Automation Platforms (MAP) like HubSpot

Marketing analytics platforms

SaaS 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 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.