Analytics Engineer H/F Mirakl

They also address the issues faced by our customers and users, responding to various challenges related to new features, scalability, security, and usability.

Your Role

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 strongly encourage you to apply to any of our roles, even if you think you're not an exact match.
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 .