Intuitive is looking to build a modern, scalable Data as a Service (DaaS) platform to power its Digital products and support over 2,000 engineers. The goal is to enable high-throughput, low-latency data delivery through streaming pipelines, dynamic transformations, and APIs, driving discoverability, accessibility, and actionable insights. This involves defining architecture and engineering practices for self-service analytics and operational decision-making at scale, and replacing legacy processes with modern solutions.
Requirements
- Proficient in at least two major programming languages such as Python, Go, Scala, C++, or Java, with a strong understanding of software design and architecture
- Proven experience building data pipelines and working with distributed systems using technologies like Apache Spark, Kafka, Elasticsearch, Snowflake, and Airflow
- Hands-on experience with AWS, Docker, Kubernetes, Kafka, Elasticsearch, Apache Airflow, Snowflake, and Terraform
- Familiarity with CI/CD best practices for DataOps and deployment automation
Responsibilities
- Design and build scalable, distributed Data as a Service that ingest, process, and serve data from robotics, manufacturing, engineering, and clinical sources in real time and batch modes
- Develop and maintain robust APIs, data services, and tooling to provide internal teams with secure, efficient, and intuitive access to high-quality data
- Implement CI/CD practices for data services, including automated testing for data quality, service reliability, and schema evolution
- Championing a self-service data culture by building discoverable, well-documented data products and guiding teams toward empowered, autonomous data access
- Act as a technical leader within the data domain driving best practices, mentoring teammates, and continuously improving how data is produced, shared, and consumed across the organization
- Partner with engineering, analytics, and business stakeholders to evolve data contracts and models that support emerging use cases and ensure semantic consistency
Other
- Solid quantitative background in Computer Science, Engineering, Physics, Math, or 8–10+ years of hands-on experience in a technically demanding role
- Strong collaborator who actively contributes to code reviews, system design discussions, sprint planning, and KPI evaluations to drive team excellence and technical quality
- Minimum a bachelor's or master's degree in computer science, information technology, or a related field.
- Experience working on Data Platform or Infrastructure Engineering teams
