Momence
SaaS
RevenueOperationsAnalyticsEngineer
Neural analysis suggests this role is
optimal for mid candidates.
“Revenue Operations Analytics Engineer at Momence. Skills: Data engineering, Analytics, Go-to-market strategy, Data infrastructure, Data pipelines, Data modeling, Analytics, Insights, RevOps systems, Automation, Predictive analytics. Build and maintain data pipelines from APIs, third-party tools, and other sources. Manage and optimize our data warehouse (Snowflake) and existing PostgreSQL systems”
Industry & Context.
Uncover insights; Simplify operations
Must be legally authorized to work in the country you're applying for, Xplor does not sponsor visas
What They're Looking For.
Must Have
SQL skills, dbt, Python for data processing and automation, Data warehousing, Snowflake, PostgreSQL, BI tools, Looker, CRM, funnel, pipeline, and revenue data, Ability to build clean, analytics-ready datasets
Nice to Have
Web scraping or non-traditional data ingestion, Predictive modeling or applied ML, Experience supporting Sales / Marketing / RevOps teams, AWS or cloud data infrastructure experience
What You'll Do.
Build and maintain data pipelines from APIs
Manage and optimize our data warehouse (Snowflake) and existing PostgreSQL systems
Lead the migration from PostgreSQL to Snowflake
including schema design and data validation
and scalability across revenue systems
Design and maintain dbt models that power core revenue metrics
reusable datasets for reporting and analytics
Define and improve data modeling standards and best practices
Build and maintain dashboards (Looker) for Sales
Define and track key funnel and revenue metrics (pipeline
Deliver ad hoc analysis to support go-to-market decisions
Build systems for lead enrichment
Develop and iterate on lead scoring models
Integrate data across CRM
Use Python and SQL to automate and streamline processes
Build predictive models such as churn risk or conversion likelihood
Translate insights into actionable workflows for Sales and RevOps
How You'll Work.
Team & Collaboration
Working closely with Sales, Marketing, and RevOps teams
Full Job Description
Momence under Xplor Technologies powers the experiences at the heart of everyday life. Through modern vertical software, embedded payments, and AI-powered capabilities, we help businesses in fitness, recreation, golf and club, field services, laundry, education, and other membership-based and service-based industries simplify operations, uncover insights, and elevate customer and member experiences. At Momence we’re looking for a Revenue Operations Analytics Engineer to own and scale our end-to-end revenue data stack. This is a high-impact role at the intersection of data engineering, analytics, and go-to-market strategy, working closely with Sales, Marketing, and RevOps teams. You’ll play a key role in building a modern, scalable data platform and turning data into actionable insights that directly impact revenue growth. Core responsibilities Data infrastructure & pipelines * Build and maintain data pipelines from APIs, third-party tools, and other sources * Manage and optimize our data warehouse (Snowflake) and existing PostgreSQL systems * Lead the migration from PostgreSQL to Snowflake, including schema design and data validation * Ensure data quality, reliability, and scalability across revenue systems Data modeling & transformation * Design and maintain dbt models that power core revenue metrics * Create clean, reusable datasets for reporting and analytics * Define and improve data modeling standards and best practices Analytics & insights * Build and maintain dashboards (Looker) for Sales, Marketing, and leadership * Define and track key funnel and revenue metrics (pipeline, conversion, retention) * Deliver ad hoc analysis to support go-to-market decisions RevOps systems & automation * Build systems for lead enrichment, routing, and management * Develop and iterate on lead scoring models * Integrate data across CRM, marketing tools, and internal systems * Use Python and SQL to automate and streamline processes Predictive analytics * Build predictive models su
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