2 months ago
Mexico City, MexicoStaff+
Responsibilities
- Define and drive architecture for event-driven data-processing services and lead migration to Node.js/TypeScript and Python.
- Improve engineering standards and patterns for distributed systems, observability, and reliability across a multi-service platform.
- Architect and implement asynchronous, high-volume scientific data-processing pipelines with at-least-once delivery, backpressure, and graceful degradation.
- Ensure software scalability, maintainability, and security on Kubernetes and AWS.
- Own existing services, understand their behavior, and make pragmatic evolution decisions.
- Set technical direction, lead cross-team initiatives, and mentor engineers through architectural guidance.
Requirements
- 12+ years of engineering experience, preferably in a SaaS environment.
- Ideally a degree in Computer Science, Software Engineering, or equivalent experience.
- Strong written and spoken English communication skills.
- Strong proficiency with Node.js/TypeScript and Python for production backend services.
- Advanced experience with asynchronous processing and distributed, event-driven systems.
- Experience with message buses, GraphQL, RESTful APIs, automated testing, unit tests, and integration tests.
- Advanced experience with large data-processing platforms such as Spark, Databricks, or Snowflake.
- Experience managing state across message buses, relational databases, caches, and other data stores.
- Production AWS experience and solid understanding of Kubernetes.
- Proficiency with CI/CD tools such as GitHub Actions.
- Knowledge of Agile software development practices.
- Experience setting technical direction, leading cross-team initiatives, mentoring engineers, and providing architectural guidance.
- Scala or other JVM-language experience, Kafka-based architectures, complex data pipelines, schema management, incremental processing, GCP, cloud portability, cloud-native technologies, or life-sciences/R&D data-management experience are advantageous.
Benefits
- Remote-friendly work environment
- Collaborative global team
- Opportunity to work on scientific research and drug-discovery software
- Equal opportunity and inclusive workplace
Tech Stack
Apache KafkaApache SparkAWSDatabricksGitHub ActionsGraphQLKubernetesNode.jsPythonScalaSnowflakeTypeScript
About Dotmatics
Dotmatics builds cloud-based R&D scientific software that unifies biology, chemistry, and data management workflows for biopharma, chemicals/materials companies, and academic labs; products include Luma, ELN, GraphPad Prism, Geneious, SnapGene, Protein Metrics, and LabArchives. The company sells SaaS and enterprise licenses for data integration, analysis, and decision support, is headquartered in Boston, and operates as a Siemens company following its acquisition.