Data Engineer Luxurynsight Luxurynsight
AI-powered SaaS platforms for luxury, fashion, and beauty industries.
Permanent
Paris
A few days home
55K to 60K € a year
> 3 years
5 years of study
Skills we're looking for
Observation skills
Teamwork
Autonomy
Agile methodologies
Trend forecasting
+16
You'll be part of
50 employees
Artificial Intelligence / Machine Learning
Big Data
Luxury
Average age: 30
Founded in 2011
56%
44%
Employee turnover: 4
Luxurynsight Group provides a suite of AI-powered SaaS platforms to over 80 luxury, fashion and beauty Groups, Maisons and retailers. It supports them in unparalleled data-driven analytics to optimize decision making in competitive intelligence and marketing, pricing, retail or investment.
As of November 2024, Heuritech has officially joined the Luxurynsight Group. This strategic operation marks a major stepstone to provide a more complete AI offer and fulfill its ambition to become the global data intelligence provider for decision-makers in the luxury, fashion, and beauty industries.
Luxurynsight built its reputation as the trusted data partner for prestigious luxury groups and maisons such as LVMH, Kering, Richemont, L’Oréal, Dior, Bulgari, Balenciaga etc.
Heuritech is a French pioneer in AI, that bridges the gap between AI and business by empowering brands such as New Balance, Prada or Decathlon to quantify and predict what people wear by market and typology (products, colors, etc.)
Our Advisory Board includes members such as:
Christian Blanckaert (former President of Hermès International)
Stanislas de Quercize (former CEO of Van Cleef & Arpels, former CEO of Cartier)
Isabelle Gex (former President of Shiseido Fragrance, former CEO of LVMH Fragrance)
Pierre Denis (former CEO of Jimmy Choo, former CEO of Coty)
Boris Collardi (former CEO of Julius Baer Group, former Partner at Pictet)
Catherine Aymard-Yu (former China Customer Director of Van Cleef & Arpels)
Luxurynsight is the winner of VIVATECH BPI France Luxury Innovation Award 2021.
Heuritech is the winner of the primary VIVATECH Luxury Innovation Award 2017.
You'll be working on
Context
Our full data pipeline starts with the crawling and ingestion of massive volumes of social media & physical events data, which are then analyzed by our computer vision models. These predictions mapped to fashion trends and aggregated into time series that feed the metrics and forecasts at the core of our product.
Team
The Data Engineering team owns this entire pipeline: from crawling and ingestion, through transformation and orchestration, to making reliable, well-structured data available to the rest of the company, Data Science, Product, and beyond. We’re responsible for the health, scalability, and evolution of the data stack that everything else at Heuritech is built on.
Our stack is built around Snowflake, dbt, Airflow, Celery, K8s, AWS, and Datadog.
Role
As a Data Engineer, your mission will be to build, maintain, and scale the systems that turn raw crawled data into trustworthy, usable data for the whole company. This includes:
designing and maintaining Airflow DAGs and orchestration logic
building and evolving dbt models and transformations in our Snowflake data warehouse
improving the reliability, monitoring, and data quality of our pipelines
working on the crawling stack that feeds our pipeline, and its infrastructure
contributing to internal tools that make data more accessible across teams
exploring and prototyping new tools or architectures to improve how we orchestrate and process data
You’ll have real ownership over the projects you’re staffed on, with the autonomy to shape the approach and drive improvements as you see fit.
We're looking for
What we’re looking for
You have several years of experience in Data Engineering or Software Engineering with a strong data focus (ideally 3-5+ years). You’re comfortable owning the full lifecycle of a data pipeline from ingestion to orchestration to modeling and you have a good instinct for making data systems robust, observable, and easy to maintain.
You’ve worked with large volumes of data and know how to think about scalability, both on the software and infrastructure side. You’re able to move from prototype to industrialized, production-grade solutions, and you know how to structure, test, and document your code so others can build on it.
Required skills
Strong proficiency in Python, environments and dependencies tooling such as uv
Solid SQL skills, data modeling knowledge, and experience with dbt or similar transformation frameworks
Hands-on experience with workflow orchestration (Airflow or equivalent)
Experience with a modern cloud data warehouse (Snowflake or equivalent)
Familiarity with CI/CD practices
Knowledge of version control with Git
Comfortable in Linux and/or macOS environments, writing and executing bash scripts
Nice-to-have skills
Experience with Celery or other task queue systems
Experience with web crawling / scraping pipelines
Experience with Kubernetes and containerization (Docker)
Experience with cloud platform (AWS or equivalent)
Understanding of agile project management methodologies
Experience with observability/monitoring tools such as Datadog
Familiarity with OpenTelemetry or equivalent for observability (traces, metrics, etc.)
Comfortable leveraging AI tools in your workflow (e.g. Claude), including building custom skills or integrating MCP servers
Soft skills
You take ownership and work autonomously, given a project, you know how to engage with stakeholders, gather the requirements you need, and lead it end-to-end from initial scoping to implementation and communication of the results. We place a lot of value on initiative, we’re looking for someone who naturally spots problems and proposes solutions on their own.
As we’re an international company, you’re comfortable communicating in English, both written and spoken.
Benefits
How we hire
First call to get to know each other and talk about the open position
Technical test
Meeting with the Data Engineering team to debrief the technical test and meet your future colleagues
Meeting with the CTO
Key figures
In short
Founding year
2011
Employees
50
Average age
30
Turnover rate
4
Gender
44%
56%
