Join Nextdata and Shape the Future of Data!
Nextdata is on a mission to make data mesh principles a reality at enterprise scale. Founded by Zhamak Dehghani, the creator of the Data Mesh, we're pioneering a data-mesh-native platform—Nextdata OS—that empowers developers to share data responsibly through data product containers. We're transforming how data is created, shared, discovered, and used, making it more connected, faster, and fairer than ever before.
Are you passionate about ensuring the highest quality in complex systems? Do you thrive on breaking things to make them better? We're seeking a dedicated Quality Assurance Engineer to ensure the excellence of Nextdata OS across various deployments. If you have a knack for enhancing CI/CD pipelines and a love for data and analytics tools, this is the role for you!
Your Impact
Ensure Product Quality: Oversee the quality of Nextdata OS in Kubernetes-based stateful systems with multiple components. Enhance Testing Infrastructure: Develop and maintain our CI and testing infrastructure, including large-scale performance and upgrade tests. Collaborate Closely: Work hand-in-hand with the engineering team and customer-facing field team to deliver the best user experience. Break and Improve: Challenge and misuse our latest features to identify weaknesses and ensure robustness. Interact with Data Tools: Engage with various data and analytics tools like Snowflake, Spark, and S3. Support Compliance Efforts: Assist in meeting compliance requirements such as SOC 2 by ensuring our testing practices adhere to industry standards. Prototype Quickly: Utilize Python and other programming languages for rapid prototyping and testing. Leverage Cloud Infrastructure: Work with cloud platforms including Kubernetes (especially managed Kubernetes), Google Cloud, AWS, and Azure. Drive Continuous Improvement: Optimize build and release processes to reduce software lead time. Embrace Data Applications: Apply your curiosity and passion for data in ML and analytics applications.
What We're Looking For
Extensive QA Experience: 7+ years in Quality Assurance Engineering, including implementing large-scale testing infrastructure for system engineering. Data and Analytics Tools: Experience with tools like Snowflake, Spark, S3, etc. CI/CD Expertise: Proficient in continuous integration and deployment, with a track record of optimizing build and release processes. Programming Skills: Proficient in Python and/or other programming languages; comfortable with quick prototyping. Cloud Infrastructure Knowledge: Experience with Kubernetes (especially managed Kubernetes), Google Cloud, AWS, and Azure. Data Application Passion: Curiosity and experience in data, machine learning, and analytics applications. Compliance Awareness: Understanding of compliance standards like SOC 2 and their impact on QA processes.
Nice to Haves
Data Mesh Understanding: Familiarity with data mesh concepts and implementations. Open Source Contributions: Experience contributing to big data/analytics open-source projects or internal data infrastructure products. Analytical Communication: Ability to quantify the value of analyses and present findings compellingly. Test-First Development: Demonstrated commitment to test-first data pipeline development.