Staff Software Engineer - Data Ingestion

RipplingSeattle, WA
$189,000 - $315,000Onsite

About The Position

The Data Cloud team is building an end-to-end analytics and business intelligence system for customers, aiming to replace the need for separate Data Lakes, Data Warehouses, and data pipelines. The system will encompass ingestion, transformation, lineage, data catalogs, and visualization. Rippling is uniquely positioned as the source for much of this data, enabling an out-of-the-box solution. The team is also exploring the use of ML and LLMs for automated insight generation and conversational analytics experiences. The data pipelines product has recently launched to beta customers with strong demand for over 100 connector types. As it moves to General Availability, this will expand to thousands of connectors for hundreds of thousands of customers, processing billions of rows of data daily to power analytics and AI-based products. The system supports API-based integration, JDBC, and Open Telemetry data ingestion. The role involves working with agentic development and handling pipelines that sync billions of rows of data daily across a multi-tenant system serving tens of thousands of customers.

Requirements

  • 8+ years of experience in software development, preferably in fast-paced, dynamic environments.
  • Solid understanding of CS fundamentals, architectures, and design patterns.
  • Proven track record in building large-scale applications, APIs, and developer tools.
  • Excellent at cross-functional collaboration, able to articulate technical concepts to non-technical partners.
  • Thrive in a product-focused environment and are passionate about making an impact on customer experience.

Nice To Haves

  • Contributing to open-source projects (Apache Iceberg, Parquet, Spark, Hive, Flink, Delta Lake, Presto, Trino, Avro).

Responsibilities

  • Develop high-quality software with attention to detail using tech stacks like Python, Apache Kafka, Iceberg, Temporal.
  • Create Data pipelines and processing products used at large scale.
  • Create data platforms, data lakes, and data ingestion systems that work at scale.
  • Have clear ownership of one or many products, APIs or platform spaces.
  • Build and grow engineering skills in different challenging areas and solve hard technical problems.
  • Influence architecture, technology selections, and trends of the whole company.

Benefits

  • Competitive salary
  • Benefits
  • Equity
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