# Software Engineer, Data Platform **Company:** [Ramp](https://scaleengineer.com/companies/ramp) Ramp is seeking a Software Engineer for their Data Platform team to build infrastructure and tools that enable machine learning and data science workflows. This role focuses on developing platforms that support the ML development lifecycle, working closely with applied scientists, AI engineers, and risk engineers to build scalable, cost-efficient systems across the analytics and machine learning stack. **Role:** Data Platform Engineer **Seniority:** Mid **Locations:** New York, NY (HQ) **Salary:** 168000–324500 USD [Apply](https://jobs.ashbyhq.com/ramp/bca0346c-b843-4795-96df-6091f51e421b) Canonical: https://scaleengineer.com/jobs/ramp/software-engineer-data-platform --- ## Responsibilities - ML Platform Development: Build and integrate components of Ramp's Analytics Platform and Machine Learning Platform - Tool Development: Create tools that improve agility and data experience for Applied Scientists, AI Engineers, and Risk Engineers - Cross-team Collaboration: Partner with stakeholder teams on building and productionizing machine learning applications - System Architecture: Design and build reliable, scalable, maintainable, and cost-efficient systems across the entire technology stack - Infrastructure Management: Manage and optimize cloud infrastructure for data and ML workloads - Pipeline Development: Build and maintain data pipelines and workflow orchestration systems - Performance Optimization: Optimize system performance, cost efficiency, and reliability of data platform components ## Requirements ### education - {"name":"Computer Science Degree","description":"Bachelor's degree in Computer Science, Engineering, or related technical field preferred"} ### technical - {"name":"Workflow Orchestration","description":"Experience with workflow orchestrators like Airflow, Dagster, or Prefect"} - {"name":"Cloud Infrastructure","description":"Experience building infrastructure on AWS, GCP, or Azure"} - {"name":"Database Knowledge","description":"Knowledge of SQL and experience with Snowflake, Redshift, BigQuery, or similar databases"} - {"name":"Python Programming","description":"Strong Python programming skills for data platform development"} - {"name":"ML Understanding","description":"Intuition around analytics and machine learning with empathy for data science workflows"} ### experience - {"name":"Data Platform Experience","description":"3+ years of experience in data engineering, platform engineering, or related field"} - {"name":"Cloud Infrastructure","description":"Proven experience building and managing cloud infrastructure at scale"} - {"name":"ML Infrastructure","description":"Experience working with machine learning infrastructure and data science teams"} ## Skills ### required - {"name":"Python","description":"Strong proficiency in Python for data platform and infrastructure development"} - {"name":"SQL","description":"Advanced SQL skills for data querying and transformation"} - {"name":"Workflow Orchestration","description":"Hands-on experience with Airflow, Dagster, or Prefect"} - {"name":"Cloud Platforms","description":"Experience building infrastructure on AWS, GCP, or Azure"} - {"name":"Data Warehousing","description":"Experience with Snowflake, Redshift, BigQuery, or similar platforms"} - {"name":"ML Intuition","description":"Understanding of analytics and machine learning workflows"} ### preferred - {"name":"AWS Expertise","description":"Deep expertise with Amazon Web Services"} - {"name":"Online ML Systems","description":"Previous experience building online machine learning systems"} - {"name":"Feature Store","description":"Experience building and maintaining feature stores"} - {"name":"Terraform","description":"Infrastructure as Code experience with Terraform"} - {"name":"Datadog","description":"Monitoring and observability experience with Datadog"} - {"name":"Streaming Systems","description":"Experience building real-time streaming data systems"} ## Tech stack ### tools - {"name":"Terraform","description":"Infrastructure as Code tool for cloud resource provisioning"} - {"name":"Datadog","description":"Monitoring and analytics platform for infrastructure and applications"} ### others - {"name":"AWS","description":"Primary cloud platform for infrastructure deployment"} - {"name":"GCP","description":"Google Cloud Platform for cloud infrastructure"} - {"name":"Azure","description":"Microsoft cloud platform alternative"} - {"name":"Feature Store","description":"ML infrastructure for managing and serving features"} - {"name":"Streaming Systems","description":"Real-time data processing infrastructure"} ### databases - {"name":"Snowflake","description":"Cloud data platform for analytics and data warehousing"} - {"name":"Redshift","description":"AWS cloud data warehouse solution"} - {"name":"BigQuery","description":"Google Cloud serverless data warehouse"} ### languages - {"name":"Python","description":"Primary programming language for data platform development and ML infrastructure"} - {"name":"SQL","description":"Essential for data querying, transformation, and database operations"} ### frameworks - {"name":"Airflow","description":"Workflow orchestration platform for managing data pipelines"} - {"name":"Dagster","description":"Modern data orchestrator for building and maintaining data assets"} - {"name":"Prefect","description":"Workflow management system for data engineering pipelines"} ## Benefits ### benefits - {"name":"Health Insurance","description":"100% medical, dental & vision insurance coverage for employees, partially covered for dependents"} - {"name":"One Medical","description":"Annual membership to One Medical primary care service"} - {"name":"401k Match","description":"Employer match on 401k contributions made while employed by Ramp"} - {"name":"Flexible PTO","description":"Unlimited paid time off policy"} - {"name":"Fertility Benefits","description":"Fertility HRA up to $10,000 per year"} - {"name":"Parental Leave","description":"Comprehensive parental leave policy"} - {"name":"AI Tools","description":"Unlimited AI token usage for productivity enhancement"} - {"name":"Pet Insurance","description":"Pet insurance coverage for employees"} - {"name":"Home Office","description":"Centralized home-office equipment ordering for all employees"} - {"name":"Wellness Stipend","description":"Health and wellness stipend for fitness and wellbeing"} - {"name":"Office Perks","description":"In-office lunch, snacks, drinks, and other amenities"} - {"name":"Travel Budget","description":"Budget for intra-office travel between locations"} - {"name":"Relocation Support","description":"Relocation assistance to NYC or SF as needed"} ## Compensation - **max:** 324500 - **min:** 168000 - **currency:** USD - **stockOptions:** true ## Interview process ### steps - {"name":"Initial Screen","description":"Phone or video screening with recruiting team to discuss background and interest"} - {"name":"Technical Phone Screen","description":"Technical discussion with engineering team member covering system design and coding concepts"} - {"name":"Take-Home Assignment","description":"Practical coding exercise related to data platform engineering challenges"} - {"name":"Virtual Onsite","description":"Multiple rounds including system design, coding interview, and behavioral discussions"} - {"name":"Team Fit Interview","description":"Cultural fit assessment and discussion with potential team members and manager"} - {"name":"Final Interview","description":"Leadership interview focusing on career goals and alignment with company values"} ## Full description # **About Ramp** At Ramp, we’re rethinking how modern finance teams function in the age of AI. We believe AI isn’t just the next big wave. It’s the new foundation for how business gets done. We’re investing in that future — and in the people bold enough to build it. Ramp is a financial operations platform designed to save companies time and money. Our all-in-one solution combines payments, corporate cards, vendor management, procurement, travel booking, and automated bookkeeping with built-in intelligence to maximize the impact of every dollar and hour spent. More than 50,000 businesses, from family-owned farms to e-commerce giants to space startups, have saved $10B and 27.5M hours with Ramp. Founded in 2019, Ramp powers the fastest-growing corporate card and bill payment platform in America, and enables over $100 billion in purchases each year. Ramp’s investors include Lightspeed Venture Partners, Thrive Capital, Sands Capital, General Catalyst, Founders Fund, Khosla Ventures, Sequoia Capital, Greylock, Redpoint, and ICONIQ, 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](https://www.fastcompany.com/91038883/ramp-most-innovative-companies-2024) list and LinkedIn’s [Top U.S. Startups](https://www.linkedin.com/pulse/linkedin-top-startups-2024-50-us-companies-rise-linkedin-news-hxote/?trackingId=uBI29YlAOxikbTI7cdvG4g%3D%3D) for more than 3 years, as well as the Forbes [Cloud 100](https://www.forbes.com/sites/richardnieva/2024/08/06/ramp-cloud-100/), CNBC [Disruptor 50](https://www.cnbc.com/2024/05/14/ramp-cnbc-disruptor-50.html), and TIME Magazine’s 100 [Most Influential Companies](https://time.com/collection/time100-companies-2023/6285147/ramp/). **About the Role** The Data Platform builds infrastructure and tools that enable Ramp to realize business value from data. We partner closely with stakeholder teams to build this infrastructure and the applications on top of it. This role is particularly focused on building platforms that support the data science development lifecycle. 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. **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. ## **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. ## **Other notices** Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. _Beware of recruiting scams: Ramp will only contact you through official @_[_Ramp.com_](http://Ramp.com) _email addresses and will never ask for payment or sensitive personal information during the hiring process._ [Ramp Applicant Privacy Notice](https://ramp.com/legal/applicant-privacy-notice)