5 publicaciones de empleo destacadas de data scientist en 09400 el sifón cdmx (¡Están contratando!)

Staff Software Engineer - Data Processing & Execution Platform
Dotmatics —Ciudad de México, CDMX
- Microsoft Excel
- Administración de personal
- Informática
Digital Media Strategist - MX
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- Contacto por teléfono
- Microsoft Excel
- Inglés
- Licenciatura
AI Presales
SDG Group —Ciudad de México, CDMX
- Trabajo híbrido
- Español
- Azure
- Doctorado
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Senior Data Scientist, DTC
Levi Strauss & Co. —Centro (Área 1), CDMX
- Tiempo completo
- Doctorado
- Informática
- Maestría
Postulación rápida
6d
Assistant Scientist
Colgate-Palmolive —Ciudad de México, CDMX
- Administración de personal
- Inglés
- Licenciatura
1h

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Staff Software Engineer - Data Processing & Execution Platform

Dotmatics -
Ciudad de México, CDMX

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Información del empleo

Cualificaciones

Microsoft Excel
Administración de personal
Node.js
Informática
Ingeniería de software
Kubernetes
Spark
Inglés
Google Cloud Platform
JavaScript
Scala
Capacitación
Desarrollo de software
Kafka
GraphQL
SaaS
TypeScript
Habilidades de comunicación
Python

Descripción completa del empleo

Our Why At Dotmatics

At Dotmatics, a Siemens company, we believe science, data, and decision-making must be deeply intertwined for innovation to thrive. Our Portfolio includes Luma, LumaLab Connect, ELN Platform, Graphpad Prism, Geneious, SnapGene, Protein Metrics, OMIQ, FCS Express, LabArchives, NQuery, EasyPanel, SoftGenetics and Virscidian.

We have a vision for a new Lab of the Future that will change the future of scientific research.

We have created the world’s most comprehensive digital science platform – best-of-breed software applications already used by more than 2 million scientists, together in a single ecosystem united by a powerful, flexible enterprise data platform. This is not flat data buried away in digital graveyards. This is dynamic, multi-dimensional decision-making.

Scientific enterprises need a new level of effectiveness to achieve tomorrow’s breakthroughs. Illness will not wait. The biosphere will not wait. We are tireless in our vision, because the time for innovation is now.

Shaping the Future of Science At Dotmatics

Our global team of more than 800 colleagues are dedicated to supporting our customers in over 180 countries. Together, with our scientific community of users, we accelerate scientific innovation in order to make the world a healthier, cleaner, and safer place to live.

You’ll join a collaborative, global team pushing the boundaries of scientific innovation. Your ideas and efforts will have a tangible impact, accelerating scientific progress and discovery. We offer a dynamic, remote-friendly environment that fosters high integrity and collaboration, empowering you to excel. Dotmatics is a company built by scientists, for scientists. Combined, we are now the world’s largest cloud-based scientific research R&D platform. We need your help to keep growing and pioneering the future.

We are Science Driven. We are Customer Centric. We are Better Together.

What do we Need:

As a Staff Software Engineer, you will be the technical lead for the data processing and execution platform - a set of services that take user-initiated operations (data commits, transformations, workflows) and execute them reliably across shared compute infrastructure. This is a distributed, event-driven system with multiple services coordinating through asynchronous message passing.

This is no ordinary engineering role - this is working on a product with real world meaning - a product that helps define the way scientists works, helping bring medicine to market quicker, finding cures for diseases faster
This is LUMA

In this role, you will:

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

We are looking for candidates with 12+ years of engineering experience, preferably in a SaaS environment, ideally with a degree in Computer Science, Software Engineering, or equivalent. Excellent written and spoken English communication skills are essential.

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

Why this role is interesting:

You're not maintaining a system in steady state. You're taking a complex, production-proven execution platform and leading its evolution - migrating to a new tech stack while keeping it running reliably for customers doing drug discovery. The system processes real scientific data through multi-step pipelines on shared compute infrastructure, with all the distributed systems challenges that implies: multi-tenancy, cancellation, crash recovery, and coordinating state across multiple data stores. If you enjoy understanding how complex systems actually work, regardless of what language they happen to be written in, and then making them better - this is the role.

Research shows us the confidence gap and imposter syndrome can get in the way of meeting outstanding candidates, so please don’t hesitate to apply — we’d love to hear from you.

By submitting your application, you agree that Dotmatics may collect your personal data for recruiting, global organization planning, and related purposes. Dotmatics Privacy Notice explains what personal information we may process, where we may process your personal information, our purposes for processing your personal information, and the rights you can exercise over Dotmatics use of your personal information.

Dotmatics is an equal opportunity employer. We are a welcoming place for everyone, and we do our best to make sure all people feel supported and connected at work.

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