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Fullstack Software Engineer - Business Solutions

Оценка ИИ

Высокий балл обусловлен сильным брендом компании в сфере ИИ, современным стеком технологий и возможностью работать над продуктами, которые реально влияют на бизнес крупнейших мировых корпораций. Наличие удаленного формата работы также является большим плюсом.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует уверенного владения как фронтендом (Vue.js/React), так и бэкендом (Python), а также опыта работы с большими данными. Процесс отбора включает несколько этапов, в том числе техническое задание или лайв-кодинг, и интервью с руководством.

Анализ зарплаты

Медиана72 000 €
Рынок60 000 € – 85 000 €
Оценка ИИ

Предлагаемая позиция в Dataiku соответствует уровню топовых технологических компаний Франции. Ожидаемая зарплата для опытного Fullstack-инженера в Париже обычно находится в диапазоне 60,000–85,000 евро в год в зависимости от квалификации.

Сопроводительное письмо

I am writing to express my strong interest in the Fullstack Software Engineer position within the Business Solutions team at Dataiku. With a solid background in developing data-intensive applications and a passion for AI-driven innovation, I am excited about the opportunity to contribute to a platform that empowers organizations to operationalize machine learning at scale. My experience in building end-to-end solutions, from intuitive front-end interfaces to robust back-end infrastructures, aligns perfectly with the requirements of this role.

In my previous projects, I have successfully utilized Python and modern JavaScript frameworks to deliver user-centric applications that simplify complex data interactions. I am particularly drawn to Dataiku's commitment to quality and its dynamic tech stack, including the integration of LLMs. I am eager to collaborate with your cross-functional teams of data scientists and industry experts to build impactful solutions for sectors like Finance and Manufacturing, ensuring that AI becomes a true business performance engine for your clients.

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Присоединяйтесь к Dataiku, чтобы создавать будущее корпоративного ИИ и решать сложнейшие бизнес-задачи с помощью передовых технологий!

Описание вакансии

Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate analytics, machine learning, and AI agents with the transparency, collaboration, and control enterprises require. Sitting above data platforms, cloud infrastructure, and AI services, Dataiku connects the full enterprise AI stack — empowering organizations to run AI across multi-vendor environments with centralized governance.

The world’s leading companies rely on Dataiku to operationalize AI and run it as a true business performance engine delivering measurable value. For more, visit the Dataiku blog, LinkedIn, X, and YouTube.

Why Engineering at Dataiku?

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 lookhere.

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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.

What you’ll need to be successful

  • 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.
  • 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.
  • 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.
  • 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.

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!

At Dataiku, you'll be part of a journey to shape the ever-evolving world of AI. We're not just building a product; we're crafting the future of AI. If you're ready to make a significant impact in a company that values innovation, collaboration, and your personal growth, we can't wait to welcome you to Dataiku! And if you’d like to learn even more about working here, you can visit our Dataiku LinkedIn page.

Our practices are rooted in the idea that everyone should be treated with dignity, decency and fairness. Dataiku also believes that a diverse identity is a source of strength and allows us to optimize across the many dimensions that are needed for our success. Therefore, we are proud to be an equal opportunity employer. All employment practices are based on business needs, without regard to race, ethnicity, gender identity or expression, sexual orientation, religion, age, neurodiversity, disability status, citizenship, veteran status or any other aspect which makes an individual unique or protected by laws and regulations in the locations where we operate. This applies to all policies and procedures related to recruitment and hiring, compensation, benefits, performance, promotion and termination and all other conditions and terms of employment. If you need assistance or an accommodation, please contact us at: reasonable-accommodations@dataiku.com


Protect yourself from fraudulent recruitment activity

Dataiku will never ask you for payment of any type during the interview or hiring process. Other than our video-conference application, Zoom, we will also never ask you to make purchases or download third-party applications during the process. If you experience something out of the ordinary or suspect fraudulent activity, please review our page on identifying and reporting fraudulent activity here.

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Навыки

  • Python
  • Vue.js
  • React
  • Angular
  • FastAPI
  • Flask
  • RESTful API
  • Machine Learning
  • LLM
  • JavaScript

Возможные вопросы на собеседовании

Проверка опыта работы с основным бэкенд-стеком компании и понимания архитектуры API.

Расскажите о вашем опыте разработки масштабируемых API на Python (FastAPI или Flask). С какими сложностями вы сталкивались?

Dataiku предпочитает Vue.js, поэтому важно понять гибкость кандидата и его знания в современных фреймворках.

Каков ваш опыт работы с Vue.js или другими реактивными фреймворками? Как вы подходите к управлению состоянием в сложных интерфейсах?

Вакансия связана с Business Solutions, где работа с данными является ключевой.

Опишите проект, где вам приходилось визуализировать или обрабатывать большие объемы данных в браузере. Как вы обеспечивали производительность?

Роль подразумевает ведение проекта от идеи до запуска.

Расскажите о случае, когда вы переводили приложение из стадии прототипа (PoC) в промышленную эксплуатацию. Какие аспекты безопасности и масштабируемости вы учитывали?

Проверка интереса к основной сфере деятельности компании.

Как, по вашему мнению, LLM и генеративный ИИ могут улучшить пользовательский опыт в корпоративных аналитических инструментах?

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