Staff Software Engineer - Data Processing & Execution Platform

• Define and drive system architecture for event-driven data processing services, leading the migration of key components to a Node.js/TypeScript and Python ecosystem
• Contribute to and improve engineering standards, patterns, and best practices for distributed systems, observability, and reliability across a multi-service platform coordinated through Kafka, GraphQL and RESTful APIs
• Architect and implement asynchronous data processing pipelines for high-volume scientific data, with attention to at-least-once delivery guarantees, backpressure, and graceful degradation
• Guarantee the scalability, maintainability, and security of software solutions running on Kubernetes and AWS
• Take ownership of existing services, develop a deep understanding of their behavior, and make pragmatic decisions about how to evolve them

The Key Skills we are looking for:

• Excellent written and spoken English communication skills, with the ability to collaborate effectively across globally distributed engineering and product teams.
• Language-agnostic engineering mindset - you pick up new languages and codebases quickly, reason about distributed system design independent of any single runtime, and can be productive in an unfamiliar stack within weeks
• Advanced working experience in Asynchronous processing
• Strong proficiency in Node.js/TypeScript and Python for building production backend services
• Proven experience designing and implementing distributed, event-driven systems coordinated through message buses, GraphQL and RESTful APIs
• Experience implementing automated testing platforms, unit tests, and integration tests
• Advanced working experience with large data processing platforms such as Spark, Databricks, or Snowflake
• Experience managing state across multiple stores (e.g. a message bus, a relational database, and a cache) and the consistency challenges that come with it
• Hands-on experience with AWS in production environments and a solid understanding of Kubernetes for orchestrating workloads
• Proficiency with CI/CD tools such as GitHub Actions
• Knowledge of Agile software development practices
• Setting technical direction, leading cross-team initiatives, and leveling up other engineers through mentoring and architectural guidance

You may also have experience in:

• Scala or other JVM languages (helpful for understanding existing services during migration)
• Message-based architectures using Kafka (consumer groups, partitioning, delivery semantics)
• Background in complex data pipelines, schema management, and incremental processing
• Exposure to AWS and/or GCP or designing systems portable across multiple cloud providers
• Building scalable distributed systems using Kubernetes and other cloud-native technologiesExperience within Life Sciences or R&D data management