Staff Software Engineer - Data Processing & Execution Platform
RemoteMexico
Job Summary
Lead the technical direction for the data processing and execution platform, defining system architecture for event-driven services that manage user-initiated operations across shared compute infrastructure. Drive the migration of key components to a Node.js/TypeScript and Python ecosystem while architecting asynchronous pipelines with at-least-once delivery guarantees and backpressure handling. Take ownership of existing services, ensuring scalability, maintainability, and security on Kubernetes and AWS, and establish engineering standards for distributed systems coordinated through Kafka, GraphQL, and RESTful APIs. Mentor cross-functional teams and guide the evolution of production-proven systems supporting drug discovery and scientific research workflows.
Required Qualifications
- 12+ years of engineering experience
- preferably in a SaaS environment
- degree in Computer Science, Software Engineering, or equivalent
- Excellent written and spoken English communication skills
- ability to collaborate effectively across globally distributed engineering and product teams
- Language-agnostic engineering mindset
- 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
- 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
Desired Qualifications
- Scala or other JVM languages
- 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 technologies
- Experience within Life Sciences or R&D data management
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