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Analytics Engineer
Mirakl — это престижный 'единорог' из списка French Tech Next40 с сильной инженерной культурой. Позиция предлагает работу с современным стеком и реальное влияние на продукт, хотя гибридный график (всего 1 день удаленки) может подойти не всем.
Сложность вакансии
Роль требует уверенного владения современным стеком (dbt, Databricks) и опыта работы от 3 лет. Процесс отбора включает кейс-стади и несколько этапов интервью, что повышает планку для кандидатов.
Анализ зарплаты
Предлагаемая роль Analytics Engineer в Бордо/Париже соответствует рыночным ожиданиям для уровня Middle/Senior. В Париже зарплаты обычно на 10-15% выше, чем в Бордо, но Mirakl как крупный scale-up обычно предлагает конкурентоспособные пакеты, включающие бонусы.
Сопроводительное письмо
I am writing to express my strong interest in the Analytics Engineer position at Mirakl. With over three years of experience in data engineering and analytics, I have developed a deep proficiency in building scalable data models and robust transformation pipelines using dbt and SQL. Having worked with modern data stacks, I am particularly impressed by Mirakl's commitment to integrating AI-powered workflows and agentic commerce infrastructure, and I am eager to contribute to this evolution.
In my previous roles, I have successfully bridged the gap between raw data and actionable business insights by partnering closely with product stakeholders. I am highly skilled in dbt core, Databricks, and Metabase, which aligns perfectly with your current tech stack. My experience in implementing advanced analytics methods, such as cohort analysis and time-series forecasting, will allow me to provide the high-quality data products necessary to fuel Mirakl's next phase of growth.
I am excited about the opportunity to join a French Tech Next40 company and work alongside a talented global team. I am confident that my technical expertise and proactive problem-solving approach make me an excellent fit for your Paris or Bordeaux office. Thank you for considering my application.
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Описание вакансии
About Mirakl:
Founded in 2012, Mirakl has been at the forefront of marketplace innovation, empowering every business to compete in the platform economy.
Today, Mirakl’s operating system combines an enterprise marketplace solution (Mirakl Platform) that enables retailers and B2B organizations to launch, scale, and operate marketplaces and dropship, AI-powered multichannel selling (Mirakl Connect), retail media (Mirakl Ads) and an agentic commerce infrastructure (Mirakl Nexus).
With dual headquarters in Boston and Paris, Mirakl helps a global ecosystem of 450+ marketplaces (B2C and B2B) and a network of over 100k third-party marketplace sellers. Brands like Macy’s, Decathlon, Carrefour, Asos, and Airbus Helicopters use Mirakl to grow their businesses in new and remarkable ways.
For more information: www.mirakl.com.
Mirakl in Numbers:
- 🗓️ Founded in 2012 | Member of French Tech Next40
- 👥 750+ employees in 9 offices worldwide: Paris, Barcelona, Bordeaux, Boston, London, Munich, New York, Sydney, Tokyo
- 🇫🇷 350+ Mirakl Tech teams members mainly based in France
- ⚙️ 5 Saas Solutions
Our Values:
Working at Mirakl means accelerating your career alongside ambitious, passionate, and supportive colleagues. We're proud of the diversity of backgrounds, perspectives, and experiences that make our teams unique.
Our 5 values guide how we collaborate:
- 💡 Work Hard Together: Teamwork and collaboration are the foundation of our success
- 🏆 Get Things Done: We prioritize action and efficiency for impactful results
- 🚀 Go Above & Beyond: We tackle challenges proactively and always aim for excellence
- 🎓 Succeed Through Expertise: Knowledge sharing and continuous learning are core to our culture
- 🤝 Satisfy & Empower Clients: We're committed to our clients' success
Your Role
Location : Paris or Bordeaux (1 day remote per week)
Contract: full-time permanent
We're looking for an Analytics Engineer to join our data team at a pivotal moment. As Mirakl scales, data isn't just supporting decisions, it's powering them. From product strategy to AI-driven workflows, everything we build needs a rock-solid data foundation.
You'll be at the intersection of engineering and analytics, transforming raw data into the insights and intelligence that fuel our next phase of growth. This isn't a "maintain the status quo" role, it's a chance to shape how data flows through the entire organization.
What You'll Do
Build Data Products That Move the Business Forward
- Partner with product and business stakeholders to understand needs and constructively challenge requirements, and ensure data products deliver actionable value
- Develop and maintain scalable data models, comprehensive semantic layer (documentation) and robust transformation pipelines to convert raw data into analytics-ready datasets
- Build and maintain dashboards guaranteeing reliable access to critical performance indicators
Shape the Future of Analytics at Mirakl
- Enable self-service analytics and emerging agentic solutions empowering users to independently discover insights and optimize workflows.
- Drive adoption of analytics solutions through user training, responsive support and incident resolution.
- Continuously refine data solutions and workflows by monitoring usage metrics and gathering user feedback to improve quality, reliability, and usability.
Your stack
- Data Platform: Databricks
- ELT & Transformation: dbt core, Airbyte
- Languages: SQL, Python
- BI & Visualization: Metabase
What We're Looking For
Must-haves
- 3+ years as an Analytics Engineer or similar data & analytics role
- Proficiency in SQL for data manipulation and automation
- dbt experience and deep understanding of modern analytics engineering (version control, automated testing, CI/CD)
- Ability to implement advanced analytics methods (cohort analysis, time series forecasting, etc.)
- Data visualization expertise with tools like Metabase, Superset, Tableau, or similar
- Strong problem-solving skills, attention to detail, and the ability to work in a fast-paced environment.
- Excellent communication skills to work with technical and non-technical stakeholders
- Proficient in professional English, both written and spoken
Nice to have
- Hands-on experience with AI-powered or agentic tools
- Experience in the ecommerce or marketplace ecosystem
- Python for analytics and automation
Why Join Now?
This is a rare opportunity to join a scale-up that's already proven its model and is now accelerating. You'll have:
- Real impact: Your work directly influences business decisions, go-to-market strategy, and company direction
- Growth trajectory: As we scale, so do the challenges and your opportunities
- Modern stack: We invest in best-in-class tools and emerging AI/agentic technologies
Collaborative culture: Work with smart, driven people across product, engineering, and business teams
Recruitment Process
- An initial call with the recruiter.
- Case study + debrief with your future Manager and a team member
- Values interviews with colleagues from other teams to ensure mutual fit
The STAR method and structured interviews will hold no secrets for you.
We welcome collaborators with their diverse perspectives and experiences to power us forward. These often far exceed conventional job requirements and help us create a culture of continuous learning. If you’re ready to join a global leader powering digital transformation for 450+ of the world’s most innovative retailers and B2B organizations..
We may use Artificial Intelligence (AI) solutions to help streamline our hiring process, including screening applications, analyzing resumes, and assessing responses. While AI helps us work efficiently, all final hiring decisions are made by humans. For more information, visit our AI Guidelines for Candidates and Interviews.
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Навыки
- Tableau
- Git
- Python
- SQL
- dbt
- CI/CD
- Databricks
- Airbyte
- Metabase
- Superset
Возможные вопросы на собеседовании
Проверка опыта работы с основным инструментом трансформации данных в стеке компании.
Расскажите о самом сложном проекте на dbt: как вы структурировали модели и какие тесты использовали для обеспечения качества данных?
Вакансия предполагает работу на стыке инженерии и бизнеса.
Как вы подходите к сбору требований от нетехнических стейкхолдеров, когда они просят 'просто дайте мне все данные'?
В стеке указан Databricks, важно понимать навыки оптимизации.
Какие методы оптимизации производительности SQL-запросов в среде Databricks/Spark вы применяли на практике?
Компания движется в сторону AI-решений.
Был ли у вас опыт работы с AI-инструментами или автоматизацией аналитических процессов с помощью Python?
Проверка навыков визуализации и понимания продуктовых метрик.
Опишите процесс создания дашборда в Metabase: как вы выбираете ключевые метрики и обеспечиваете удобство использования для конечных пользователей?
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