Data Platform Engineer - Analytics & ML Infra

Ramp; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Flexible PTO

Centralized home-office equipment

Health and wellness stipend

Budget for intra-office travel

Weekly coffee stipend

US-wide coverage

100% medical, dental and vision forYou

One Medical annual membership

401(k) with employer match

Fertility HRA (up to $10,000 per year)

Parental leave: 16 weeks / 8 weeks

Pet insurance

In-office perks

Job summary

Ramp is seeking a Data Platform Engineer to help build Ramp's Analytics and Machine Learning Platform. You will partner with applied scientists, AI engineers, risk engineers, and other ML developers to accelerate ML model development.

You will design and implement scalable data tooling, ensure reliable data workflows, and collaborate across teams to productionize ML applications on AWS/GCP/Azure. Strong Python and SQL skills are essential.

Qualifications

• 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.

Responsibilities

• 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-efficiency systems across the stack.

Skills

Python programming

SQL

Data analytics

Collaboration

Tools

Airflow

Dagster

Prefect

Snowflake

Redshift

BigQuery

Terraform

Datadog

Job description

Ramp is seeking a Data Platform Engineer to help build Ramp's Analytics and Machine Learning Platform. You will partner with applied scientists, AI engineers, risk engineers, and other ML developers to accelerate ML model development.

You will design and implement scalable data tooling, ensure reliable data workflows, and collaborate across teams to productionize ML applications on AWS/GCP/Azure. Strong Python and SQL skills are essential.