Senior Data Platform Engineer - ML & Workflow Orchestration

Rippling; San Francisco (CA); On-site; USD 168,000 - 280,000; Full time

Job summary

Rippling, based in San Francisco, seeks a Senior Software Engineer to work across core data and ML infrastructure, workflow orchestration, data integrations, and production systems for ML and agent workloads. You will own complex systems across multiple technical areas, not just a single stack.

This broad platform role requires strong systems-design skills, ownership of production reliability, and collaboration with product, engineering, data science, and business teams to deliver durable

Qualifications

• 5+ years of software engineering experience building backend systems, distributed systems, infrastructure, or data platforms.
• Proven track record of owning and delivering complex technical projects.
• Strong hands-on coding skills in a backend or systems language.
• Experience building production data platforms across data warehouses and lakehouses, and with orchestration systems.
• Experience with cloud infrastructure and modern deployment practices (AWS, Kubernetes, IaC).

Responsibilities

• Design, build, and operate infrastructure for data, analytics, ML, and AI workflows.
• Build reusable workflow and integration capabilities for cross-platform data movement.
• Build data access and query capabilities across warehouses, lakehouses, and operational systems.
• Strengthen data security through least-privilege access, masking, and auditing.
• Lead projects from design to production operation, including incident response and improvements.

Skills

Backend systems

Distributed systems

Data platforms

Production systems

Coding skills

Cloud infrastructure

Tools

Snowflake

Databricks

StarRocks

Iceberg

Delta Lake

Spark

Dagster

Airflow

Prefect

AWS

Kubernetes

Job description

Rippling, based in San Francisco, seeks a Senior Software Engineer to work across core data and ML infrastructure, workflow orchestration, data integrations, and production systems for ML and agent workloads. You will own complex systems across multiple technical areas, not just a single stack.

This broad platform role requires strong systems-design skills, ownership of production reliability, and collaboration with product, engineering, data science, and business teams to deliver durable