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Our Why At Dotmatics At Dotmatics, 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, MStar, 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. 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 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.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.