At Datahouse, you'll be coding and delivering high-quality software. You will collaborate on innovative solutions, translating business needs into software, designing, building efficient and scalable software, and fostering an open culture of knowledge sharing. You should be striving for excellence, taking pride in delivering high-quality codes, and have excellent problem-solving abilities.

You will be an integral part of the Engineering Team and jointly responsible for the further development and operation of our platforms. You will work as part of a small, agile software development team with interfaces to all areas of the company, develop our software system together with the team, where they use .NET 9 in a cloud-based environment (Microsoft Azure). Following the "You build it, you run it" approach, you and the team will take responsibility for the operation of our software system.

As a Principal Software Engineer | MLI at ExtraHop, you’ll work on the design and implementation of scalable systems that support our machine learning projects. You’ll work closely with data scientists, ML engineers, and cloud teams to create efficient tools and infrastructure for managing machine learning workflows – from data collection and experimentation to deployment and monitoring.

This role requires a key player to apply advanced software engineering skills to build technologies that support our drug discovery efforts. Key responsibilities include development of training data workflows for the training of machine-learning (ML) models and scalable deployment of machine-learning technologies, and creation, testing and maintenance of software systems.

This person will work with stakeholders like security, product management, QA, and customer support. They will have an opportunity to flex into a security mindset while bringing their software architecture and programming skills to build reliable, secure systems for our dbt cloud SaaS product. They will primarily be working on the Django monolith and a couple of Go micro-services.

Enhance the enterprise-grade authentication and authorization platform that enables Single Sign-On, Role Based Access Control and User and Token management. Build and maintain stable, scalable foundational services that can be leveraged by other engineering teams, based off solid architectural principles and cross-team collaboration. Design and develop reliable, secure, highly available and delightful experiences for both customer personas: the dbt Cloud admin and the end user.

Calendly is seeking a Staff Full Stack Engineer with strong technical competency and distributed systems experience, who enjoys solving complex problems with a results driven mindset, and fosters a strong sense of ownership and operational excellence. You will report to one of the Engineering Managers in our Scheduling group and will be at the forefront of building a best-in-class contact management and scheduling experience.

Collaborate closely with fellow engineers to architect and implement services required to back OneSignal’s product offerings. Help optimize a scaling strategy for our high performance Postgres and Scylla clusters. Design and optimize schemas, queries, indices, caches and more across Postgres and Scylla. Actively participate in peer code reviews and Technical Design Spec reviews, providing valuable technical insights to continuously improve our code base.

In this role, you will be responsible for building out products that serve our customers while making changes on the backend to support our continued growth. Core functions include writing code and brainstorming clever ways to improve Basis’ highly scalable real-time bidding (RTB) platform, which processes more than 350 billion auctions, each within milliseconds, every day.

Build and maintain data catalog infrastructure that connects with BI tools, warehouses, and metadata platforms. Develop and own full-stack features, from backend services and data integrations to APIs and web interfaces. Create and maintain platform connectors and adapters to unify data and metadata across sources. Help define integration standards and best practices for cross-platform data workflows.