Fullstack Software Engineer
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Requirements
• Full-Stack Development Experience: You have experience in full-stack software engineering, with experience taking an app from PoC to production. You are comfortable working across the stack—from the front-end user interface to the back-end infrastructure. • Front-End Skills: Proficiency in modern reactive front-end frameworks like Vue.js (preferred), React, or Angular. You have a deep understanding of building user-centric, interactive web applications. • Back-End Skills: Strong experience with backend development, especially with Python (FastAPI, Flask, etc.). You are familiar with RESTful API design and willing to adapt to Dataiku’s tech stack and best practices. • Experience with Data-Intensive Applications: You understand the challenges of working with large datasets and designing high-performance, data-driven applications. Experience with analytics products or data platforms is a strong plus. • Experience with Data-Intensive Applications • Customer-Oriented Mindset: You have a strong focus on solving real-world problems for customers. You understand that building an effective product means diving deep into customer use cases, iterating based on feedback, and delivering the most relevant and efficient solutions. • Customer-Oriented Mindset • Curiosity: You are excited to learn, adapt, and take on new challenges. Whether it's discussing architecture, troubleshooting issues, or writing code, you are driven to make an impact and contribute to the team’s success. • Curiosity • Tech Enthusiast: You’re genuinely passionate about AI and data-driven applications. You’re excited by the possibility of using cutting-edge AI technologies, like LLMs, to shape the future of business. • Tech Enthusiast • What does the hiring process look like? • 45 min call with a Technical Recruiter • Technical video interview with an Engineering Team Lead • Take home assignment or Live Coding session • 2 last interviews with VPs of Engineering #LI-Remote • What are you waiting for!
Benefits
• Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here. • In Business Solutions, we are building apps that leverage Dataiku’s capabilities in data and AI, focused on key enterprise use cases that need their own, user-focused UI’s and flows. We do this for customers in verticals such as Manufacturing, Life Sciences and Finance, powering key processes within their business- and operating models. In short: our work truly is part of “everyday AI”! • How you’ll make an impact • Build Innovative AI-Driven Applications: Design, develop, and deploy AI-powered applications that solve complex business problems, integrating Dataiku’s backend AI capabilities with user-centric, intuitive front-end interfaces. • Build Innovative AI-Driven Applications: • Work with Data Scientists and Industry Specialists: Collaborate with solutions engineers, data scientists, and industry experts to develop the best solutions for customers. Help define requirements and deliver state-of-the-art applications that meet user needs across different verticals such as finance, manufacturing, and life sciences. • Work with Data Scientists and Industry Specialists: • Empower Business Users: Create applications that allow expert users to work with large datasets and extract meaningful insights quickly and intuitively. Your goal is to bring complex data to life in the browser and simplify interactions with large-scale data sets. • Empower Business Users: • Drive Continuous Improvement: Take responsibility for the end-to-end lifecycle of applications—from PoC to production. Contribute to the maintenance and evolution of the tech stack and frameworks, and support new features and architecture improvements to ensure scalability and reliability. • Drive Continuous Improvement: • Collaborate Across Teams: Work closely with core teams to ensure high-quality, reusable components, provide best practices, and help make data scientists and business users autonomous in building solutions end-to-end. • Collaborate Across Teams: • Contribute to Team Growth: Help mentor new team members, participate in interviews, and contribute to onboarding processes. Bring your expertise and enthusiasm to help grow a collaborative, inclusive, and innovative team culture. • Contribute to Team Growth: