Revenue Operations Analytics Engineer (Momence)Xplor • Denver, Colorado, United States
Revenue Operations Analytics Engineer (Momence)
Xplor
- Denver, Colorado, United States
- Denver, Colorado, United States
À propos
Full-time
Department: Implementation Value Add
Division: Fitness and Wellbeing
Compensation: USD 125,000 - USD 150,000 yearly
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
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
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 such as churn risk or conversion likelihood
Translate insights into actionable workflows for Sales and RevOps
Essential qualifications
Strong SQL skills, ideally with dbt
Python for data processing and automation
A solid grasp of data warehousing, ideally Snowflake
Good knowledge of PostgreSQL
Confidence working with BI tools, ideally Looker
Familiarity with CRM, funnel, pipeline, and revenue data
Ability to build clean, analytics‑ready datasets
Nice to have
Experience with web scraping or non‑traditional data ingestion
Exposure to predictive modeling or applied ML
Experience supporting Sales / Marketing / RevOps teams
AWS or cloud data infrastructure experience
Benefits
Paid Parental Leave benefit programs
3 extra days off to volunteer and give back to your local community
Diverse & Inclusion initiatives, such as D&I Council & Global Mentorship Program
Access to free mental health support
Flexible working arrangements
Equal Employment Opportunity Xplor is proud to be an Equal Employment Opportunity employer. We’re dedicated to attracting, retaining and developing our people regardless of gender identity, ethnicity, sexual orientation, disability, veteran status, and age. All application information will be kept confidential in accordance with EEO guidelines.
Xplor is committed to the full inclusion of all qualified individuals. Accordingly, if reasonable accommodation is required to fully participate in the job application or interview process, to perform the essential functions of the position, and/or to receive all other benefits and privileges of employment, please contact us via talent@xplortechnologies.com.
To be considered for employment, you must be legally authorized to work in the country you are applying for. Xplor does not sponsor visas, at the time of hire or at any later time.
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Compétences linguistiques
- English
Avis aux utilisateurs
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