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Rippling is hiring a Senior Software Engineer to join its Data Platform team, which builds and operates infrastructure, tools, and integrations enabling teams across the company to independently deliver reliable data processing, analytics, ML, and AI workflows.
In this broad platform role, you will own complex systems across multiple technical areas rather than working within one narrow part of the stack. You will design, build, and operate infrastructure for reliable, scalable, and cost-effective data, analytics, ML, and AI workflows. Key responsibilities include:
- Design and build reusable workflow and integration capabilities that let teams independently move, process, and use data across platforms.
- Build data access and query capabilities for analytics and agent workloads to use data across warehouses, lakehouses, and operational systems.
- Build reusable platform capabilities for research, analytics, and long-running agent workflows, including orchestration, state management, retries, evaluation, observability, and result delivery.
- Strengthen data security through least-privilege access, short-lived service identities, data masking, and audit controls.
- Improve platform reliability, data quality, performance, cost, observability, and developer experience.
- Lead projects from technical design through production operation, including incident response and long-term improvements.
- Partner with product, engineering, data science, and business teams to turn repeated needs into durable platform capabilities.
- Help set technical direction and raise the engineering bar across the team.
Rippling is a San Francisco-based HR, IT, and Finance platform that has raised $1.4B+ from top investors including Kleiner Perkins, Founders Fund, Sequoia, Greenoaks, and Bedrock. The company was named one of America's best startup employers by Forbes.
Rippling values in-office collaboration and expects office-based employees (those within a defined radius of a Rippling office) to work in the office at least three days a week.
**Requirements:**
- 5+ years of software engineering experience building backend systems, distributed systems, infrastructure, or data platforms.
- Proven record of owning and delivering complex technical projects.
- Strong hands-on coding skills in a backend or systems language.
- Experience building and operating production data platforms across: data warehouses and distributed-query systems (Snowflake, Databricks, StarRocks); lakehouse storage and compute systems (Iceberg, Delta Lake, Spark, Glue, EMR); workflow orchestration systems (Dagster, Airflow, Prefect); cloud and platform infrastructure (AWS, Kubernetes, infrastructure as code).
- Experience building integrations and data-access systems that move or expose data across platforms to downstream users and applications.
- Experience owning production systems, including reliability, security, observability, cost, and incident response.
- Strong systems-design skills and sound judgment across reliability, security, scale, cost, and usability.
- Ability to work across multiple technical areas and make progress through ambiguity.
- Strong communication skills and experience working with technical and non-technical partners.
**Nice to have:**
- Experience building ML platform capabilities or training, deploying, and operating ML models in production.
- Experience building agent platforms, long-running agent workflows, or similar distributed asynchronous systems.
- Experience with ML or agent evaluation and observability using MLflow, LangSmith, or similar tools.
- Experience with data discovery, lineage, access controls, or governance systems.
