ABOUT MUTINEX

We’re an early-stage B2B SaaS startup with a proven platform, big-name clients, and millions in revenue. We’re not chasing unicorn status; we’re building a sustainable, long-lasting business (think Bowhead Whale!). Mutinex helps marketers understand their ROI and make smarter decisions with their budget.
We’re a hybrid team based in Sydney, Melbourne, and New York. We value communication, open-mindedness, and a culture of feedback. All staff receive equity (ESOP), and we offer increasing annual leave based on tenure.

THE ROLE

As a Senior Software Engineer on the DataOS team, you’ll be a key technical contributor, responsible for building and scaling DataOS, our core platform for automating data ingestion and processing for Marketing Mix Modelling (MMM).
While your primary focus is building robust and scalable data systems, this role is full-stack in nature. You’ll have the opportunity to work across our entire technology stack, contributing to our frontend applications to deliver complete, end-to-end features for our users. You’ll apply first-principles software engineering to complex data challenges, taking ownership of a high-impact domain within a fast-growing, product-led startup.

ROLE RESPONSIBILITIES

• Platform Architecture and Development: Be a key player in steering the technical design and development of DataOS. You’ll architect and build new features, evolve the platform’s architecture for scalability and maintainability, and uphold the highest standards of code quality.
• Building Scalable Data Systems: Play a crucial part in the engineering efforts to scale our data processing and warehousing solutions. This involves performance engineering, optimizing distributed systems, and designing infrastructure that can handle terabytes of data efficiently.
• End-to-End Feature Delivery: Take ownership of features from the data processing layer all the way to the user interface. You’ll work on both the backend APIs and the frontend components that consume them, ensuring a seamless user experience.
• Automated Data Quality & Observability: Go beyond simple data validation. Design and implement robust, automated frameworks for data quality assurance, error handling, and end-to-end observability across our data platform.
• Performance Optimization: Proactively identify and eliminate performance bottlenecks across the platform, from data ingestion and transformation to storage and retrieval.
• Collaboration and Mentorship: Work within a cross-functional team of product managers, data scientists, and other engineers. Share your expertise with team members, championing best practices through code reviews and technical guidance.