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Software Engineer | Data Platform

Ramp

Ramp

Software Engineering
New York, NY, USA
Posted on Dec 20, 2024

About Ramp

Ramp is a financial operations platform designed to save businesses time and money. Combining corporate cards with expense management, bill payments, vendor management, accounting automation, and more, Ramp's all-in-one solution frees finance teams to do the best work of their lives. More than 25,000 companies, from family-owned farms to e-commerce giants to space startups, have saved $1B and 10M hours with Ramp. Founded in 2019, Ramp powers the fastest-growing corporate card and bill payment platform in America, and enables over 35 billion dollars in purchases each year.

Ramp's investors include Sequoia, Founders Fund, Thrive Capital, Khosla Ventures, Greylock, Stripe, Goldman Sachs, Coatue, and Redpoint, as well as over 100 angel investors who were founders or executives of leading companies. The Ramp team comprises talented leaders from leading financial services and fintech companies—Stripe, Affirm, Goldman Sachs, American Express, Mastercard, Visa, Capital One—as well as technology companies such as Meta, Uber, Netflix, Twitter, Dropbox, and Instacart.

Ramp has been named to Fast Company's Most Innovative Companies list and LinkedIn's Top U.S. Startups for over 3 years, as well as the Forbes Cloud 100, CNBC Disruptor 50, and TIME Magazine's 100 Most Influential Companies.

About the Role

The Data Platform team develops and owns the systems that enable Ramp's reporting and strategic decision-making, as well as integrating machine learning models into our operational systems and the product itself. As a member of the Data Platform team, you’ll build and maintain the infrastructure that enables Ramp to realize value from data. You’ll also partner with Ramp’s analytics engineers, applied scientists, software engineers, and other data professionals to build internally and externally-facing data infrastructure & products.

Our ideal candidate is excited about building systems for data collection, processing, storage, and retrieval, and is also passionate about making these systems observable, reliable, scalable, and highly automated.

What You’ll Do

  • Build and integrate the components of Ramp's Analytics Platform and Machine Learning Platform.

  • Build tools that improve the agility and data experience of Ramp's Data Scientists, Analytics Engineers, Engineers, and Operations teams.

  • Build the batch and streaming data pipelines critical to Ramp’s daily operations using Airflow, Snowflake, ClickHouse, Kafka, and other data processing technologies.

  • Collaborate with stakeholder teams on building and productionizing analytical products and machine learning systems.

  • Build reliable, scalable, maintainable, and cost-efficient systems across the stack.

What You Need

  • Experience with workflow orchestrators like Airflow, Dagster, or Prefect.

  • Experience building infrastructure on AWS, GCP, or Azure.

  • Knowledge of SQL and experience with Snowflake, Redshift, BigQuery, or similar databases.

  • Intuition around analytics and machine learning.

  • Strong Python programming skills.

  • Track record of building highly reliable infrastructure for data storage and processing.

Nice to Haves

  • Expertise with AWS

  • Previous experience building online machine learning systems.

  • Previous experience building a feature store.

  • Experience with Terraform and Datadog

  • Experience building streaming systems.

Benefits (for U.S.-based full-time employees)

  • 100% medical, dental & vision insurance coverage for you

    • Partially covered for your dependents

    • One Medical annual membership

  • 401k (including employer match on contributions made while employed by Ramp)

  • Flexible PTO

  • Fertility HRA (up to $5,000 per year)

  • WFH stipend to support your home office needs

  • Wellness stipend

  • Parental Leave

  • Relocation support for NY

  • Pet insurance

Other notices

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.