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Metronome is the leading usage-based billing platform built for modern software companies. With Metronome, companies can launch products faster, offer any pricing model, and streamline finance workflows without writing code.
Our platform computes millions of invoices per billing period and is scaling rapidly to accommodate new customers, saving them hours of development time and manual invoicing and enabling them to use consumption data to better serve their customers. Our customers love our product and approach, and we’re humbled to work with amazing companies like OpenAI, Databricks, NVIDIA, Confluent, and Anthropic.
You'll be joining an experienced team that includes founders who have successfully built and sold startups before. Our founders and employees also have direct experience building and scaling teams through massive growth at companies like Dropbox, Clever, and New Relic. On the back of this experience and our success-to-date, we’ve raised over $128M from leading investors including NEA, Andreessen Horowitz, General Catalyst, Elad Gil, and Workday Ventures. We’re also proud to have founders and executives of companies like Segment, Plaid, Looker, Gitlab, Confluent, HashiCorp, and Snowflake, as investors who have experienced the pain we're solving firsthand.
Metronome is seeking an experienced Data Analytics Consultant to leverage our data to produce new datasets that help our clients address a wide range of business use cases. The primary goal is to create data solutions for revenue recognition, daily revenue tracking and analysis, margin optimization, and other financial insights.
This is a contract position requiring 10-20 hours per week with potential to convert to full-time based on business needs. The role offers high visibility and impact, as you will enable our users to solve billing challenges using critical product usage and revenue data.
What You'll Do- Build data models and datasets for revenue recognition, daily tracking, and commit burn analysis to support key financial use cases
- Develop interactive dashboards and visualizations in Hex that make complex billing data accessible to stakeholders
- Evaluate and recommend improvements to Metronome's data models to better support business needs
- Create proof-of-concept predictive models for revenue forecasting, pricing optimization, and other business-critical insights
- Present findings and collaborate with cross-functional teams to understand evolving data requirements
- Conduct ad-hoc analyses to support strategic decision-making
- Your work will be critical to the core of Metronome's offering
- The Metronome team will be more well-rounded because you bring your unique perspective and skills to help create an inclusive environment focused on delivering value to our customers
- 3+ years of experience in data analytics, business intelligence, or similar roles
- Strong SQL skills with experience querying large datasets
- Proficiency with Python for data analysis and visualization
- Experience with BI tools, particularly Hex
- Background in revenue modeling, financial analysis, or SaaS metrics preferred
- Demonstrated ability to work in early-stage environments with limited data infrastructure
- Strong communication skills for presenting complex analyses to stakeholders
We don't filter based on current expertise, so at Metronome you will learn:
- AWS data stack (S3, Athena, etc.)
- Working with parquet and iceberg table formats
- Python scripting for data transformation
- Advanced data visualization techniques in Hex
- EMR for Spark jobs
The pay range for this role is $125-150/hour paid on a monthly basis.
for Full-time employees:
- Excellent medical, dental, vision, and life insurance coverage, including a One Medical membership
- Paid parental leave
- FSA (Flexible spending account)
- Retirement planning - Traditional and ROTH 401(k)
- Flexible time off
- Employee assistance program (mental health benefits)
- Culture where personal growth is highly valued
We're an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
