Intuitive is looking for a Staff Software Engineer to build a modern, scalable Data as a Service (DaaS) platform that powers its Digital products and supports over 2,000 engineers. The role aims to evolve critical components of real-time and micro-batch data pipelines, enabling high-throughput, low-latency data delivery for application development, AI/ML, and actionable insights, while also defining architecture and engineering practices for self-service analytics and operational decision-making.
Requirements
- Fluent coding with at least two of the following: Python, Go, Scala, Java, C++
- Proven experience building data pipelines and working with distributed systems using technologies like Apache Spark, Kafka, Elasticsearch, Snowflake, and Airflow
- Deep technical knowledge & experience with Data Platform components/design patterns: Event-Driven Pipelines (e.g. AWS Lambda), Message Queues (e.g. Kafka), Container Orchestration (e.g. Kubernetes), Stream Processing (e.g. Flink, Spark), Relational Databases (e.g. Postgres), Data Warehouses (e.g. Snowflake), Analytics Engineering (e.g. DBT), Workflow Orchestration (e.g. Airflow), Search Engines (e.g. Elasticsearch)
- Proven understanding of CI/CD workflows, unit testing and integration testing, and deployment patterns.
- Experience with AWS and/or GCP
- Experience with SQL and relational databases
- Experience with Terraform, Ansible, Packer + general IaC best practices
Responsibilities
- Build highly scalable distributed systems that leverage event-based and streaming data pipelines to handle ingestion and processing of robot, manufacturing, and clinical data
- Enable users by providing self-service APIs and applications to access and interact with data
- Work closely with core engineering teams to consistently evolve data models based on growing business needs
- Apply and evangelize software development best practices such as CI/CD, automated testing, infrastructure-as-code, and microservice architectures
- Effectively participate in the team’s planning, code reviews, KPI reviews, and design discussions leading to continuous improvement in these areas.
- Act as a technical supervisor within the data domain driving best practices, mentoring teammates, and continuously improving how data is produced, shared, and consumed across the organization
Other
- Exceptional quantitative background (Computer Science, Math, Physics, and/or Engineering), or at least 8-10+ years of industry experience in a quantitative role
- Ability and enthusiasm to work collaboratively and cross-functionally, and take end-to-end ownership to deliver results for customers
- Experience on a Platform team
- You enjoyed the book Designing Data-Intensive Applications by Martin Kleppman
- You’re familiar with CNCF projects and have successfully used them in the past
