Senior Software Engineer, Data Platform
About The Position
Rippling's Data Platform team builds and operates the infrastructure, tools, and integrations that enable teams across the company to independently deliver reliable data processing, analytics, ML, and AI workflows. Product and business teams own their use cases. We provide the foundations that help them move, process, and use data reliably, securely, and cost-effectively. We are hiring a Senior Software Engineer to work across core data and ML infrastructure, workflow orchestration, data integrations and movement, distributed data access, and production systems for ML and agent workloads. This is a broad platform role. You will own complex systems across multiple technical areas rather than working within one narrow part of the stack.
Requirements
- 5+ years of software engineering experience building backend systems, distributed systems, infrastructure, or data platforms.
- A 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 such as Snowflake, Databricks, or StarRocks.
- Lakehouse storage and compute systems such as Iceberg, Delta Lake, Spark, Glue, or EMR.
- Workflow orchestration systems such as Dagster, Airflow, or Prefect.
- Cloud and platform infrastructure such as AWS, Kubernetes, and 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 Haves
- 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.
Responsibilities
- Design, build, and operate infrastructure for reliable, scalable, and cost-effective data, analytics, ML, and AI workflows.
- Build reusable workflow and integration capabilities that let teams independently move, process, and use data across platforms.
- Build data access and query capabilities that let analytics and agent workloads use data across warehouses, lakehouses, and operational systems.
- Build reusable platform capabilities for research, analytics, and other 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.
Benefits
- competitive salary + benefits + equity
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
