Staff Software Engineer, Data Ingestion & Pipelines

Rippling (Netherlands); San Francisco (CA); Hybrid; USD 189,000 - 315,000; Full time

Benefits offered by this job

Equity

Competitive salary and benefits

Job summary

Rippling is hiring for a Data Cloud engineer to build an end-to-end analytics and BI system. You will replace data lake and data warehouse needs with scalable pipelines, catalogs, and visualization. You’ll work on ingestion, transformation, and data governance across thousands of connectors.

The role emphasizes ML/LLMs to deliver automated insights and a virtual data scientist assistant. The team is expanding with high-scale data workloads and multi-tenant architectures, collaborating with

Qualifications

• 8+ years of software development experience in fast-paced environments.
• Strong CS fundamentals, architectures, and design patterns.
• Proven track record building large-scale applications and APIs.
• Excellent collaboration and ability to explain technical concepts to non-technical partners.
• Bonus points for open-source contributions (Apache Iceberg, Parquet, Spark, Hive, Flink, Delta Lake, Presto, Trino, Avro).

Responsibilities

• Develop high-quality software with attention to detail using Python, Apache Kafka, Iceberg, Temporal.
• Create data pipelines and processing products used at large scale.
• Build data platforms, data lakes, and data ingestion systems that work at scale.
• Own one or more products, APIs, or platform spaces, and influence architecture.
• Grow engineering skills across challenging areas and shape technology choices across the company.

Skills

Senior software development

APIs

Cross-functional collaboration

Data systems

Tools

Apache Kafka

Iceberg

Temporal

Job description

Rippling is hiring for a Data Cloud engineer to build an end-to-end analytics and BI system. You will replace data lake and data warehouse needs with scalable pipelines, catalogs, and visualization. You’ll work on ingestion, transformation, and data governance across thousands of connectors.

The role emphasizes ML/LLMs to deliver automated insights and a virtual data scientist assistant. The team is expanding with high-scale data workloads and multi-tenant architectures, collaborating with