Software Engineer, Data Platform
Ramp
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Compensation
Salary & market context
230% above the BLS national median
BLS national median: $74,680
- $10,000
Requirements
Top requirements
- 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, and empathy for data science workflows. - Strong Python programming skills.
- 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.
Perks & setup
Benefits candidates care about
- 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 $10,000 per year) - Parental Leave - Unlimited AI token usage - Pet insurance - Centralized home-office equipment ordering for all employees - Health and Wellness stipend - In-office perks: lunch, snacks, drinks, and more - Budget for intra-office travel - Relocation support to NYC or SF (as needed) REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.
Why candidates care
Benefits & perks
- 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 $10,000 per year) - Parental Leave - Unlimited AI token usage - Pet insurance - Centralized home-office equipment ordering for all employees - Health and Wellness stipend - In-office perks: lunch, snacks, drinks, and more - Budget for intra-office travel - Relocation support to NYC or SF (as needed) REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.
Start here
Requirements
- 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, and empathy for data science workflows. - Strong Python programming skills.
- 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.
Responsibilities
What you'll do
- If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it.
- We partner closely with stakeholder teams to build this infrastructure and the applications on top of it.
- You’ll partner with applied scientists, AI engineers, Risk engineers, and other ML developers on building infrastructure and tools that enable and accelerate the development of machine learning models.
- 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 Applied Scientists, AI Engineers, and Risk Engineers. - Collaborate with stakeholder teams on building and productionizing machine learning applications. - Build reliable, scalable, maintainable, and cost-efficient systems across the stack.
Role snapshot
About the role
ABOUT RAMP
Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $100B in annualized spend flows in and out of 50,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books.
The problems are high-stakes, data-dense, and unforgiving.
We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome.
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