2 days ago
Mexico City, MexicoStaff+
Responsibilities
- Define and drive the architecture of event-driven data processing services and lead migration of components to Node.js/TypeScript and Python.
- Architect and implement asynchronous, high-volume scientific data pipelines with at-least-once delivery, backpressure, and graceful degradation.
- Improve engineering standards, distributed-systems patterns, observability, reliability, scalability, maintainability, and security across the multi-service platform.
- Own and evolve existing services coordinating through Kafka, GraphQL, and RESTful APIs across shared compute infrastructure.
- Lead cross-team technical initiatives, set technical direction, mentor engineers, and provide architectural guidance.
Requirements
- 12+ years of engineering experience, preferably in a SaaS environment.
- Strong proficiency in Node.js/TypeScript and Python for production backend services.
- Advanced experience with asynchronous processing, distributed event-driven systems, message buses, and large-scale data processing platforms such as Spark, Databricks, or Snowflake.
- Experience managing state across multiple data stores and handling consistency challenges, plus hands-on AWS production experience and Kubernetes knowledge.
- Experience with automated testing platforms, unit tests, integration tests, and GitHub Actions.
- Ability to reason across languages and unfamiliar codebases, collaborate with globally distributed teams, and communicate fluently in written and spoken English.
- Experience setting technical direction, leading cross-team initiatives, mentoring engineers, and providing architectural guidance.
- Helpful qualifications include Scala or other JVM languages, Kafka message-based architectures, complex data pipelines, schema management, incremental processing, GCP or multi-cloud design, cloud-native distributed systems, and life-sciences or R&D data management experience.
- A degree in Computer Science, Software Engineering, or equivalent is preferred.
Benefits
- Remote-friendly work environment with a focus on collaboration, integrity, and global teamwork.
Tech Stack
Apache KafkaApache SparkAWSDatabricksGitHub ActionsGraphQLKubernetesNode.jsPythonScalaSnowflakeTypeScript
Categories
BackendData Engineering
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.