Data Engineer: Build Scalable, End-to-End Data Pipelines

Luxurynsight group; Paris; On-site; EUR 65,000 - 90,000; Full time

Job summary

Luxurynsight is seeking a Data Engineer to design, build, and scale our data pipelines. You will own the end-to-end lifecycle from data ingestion to modeling and orchestration, ensuring robust, observable, and maintainable systems for the company.

You’ll work with Python, SQL, and modern cloud data tooling, contributing to a data-driven culture while collaborating with cross-functional teams in a fast-paced environment.

Qualifications

• Several years of experience in Data Engineering or Software Engineering with a strong data focus (3–5+ years).
• Own the full lifecycle of a data pipeline from ingestion to orchestration to modeling.
• Experience with large volumes of data and scalability considerations across software and infrastructure.
• Strong Python development and SQL skills, with experience in dbt or similar transformation frameworks.
• Familiarity with CI/CD practices and version control (Git).
• Comfortable working in Linux and macOS environments.

Responsibilities

• Designing and maintaining Airflow DAGs and orchestration logic.
• Building and evolving dbt models and transformations in our Snowflake data warehouse.
• Improving reliability, monitoring, and data quality of pipelines.
• Working on the crawling stack that feeds our pipeline and its infrastructure.
• Contributing to internal tools that improve data accessibility across teams.
• Exploring and prototyping new tools or architectures to enhance orchestration and processing.

Skills

Python

SQL

Data modeling

dbt

Airflow

Snowflake

CI/CD

Git

Bash

Linux

macOS

Tools

Celery

Docker

Kubernetes

AWS

Datadog

OpenTelemetry

Job description

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.

What we’re looking forYou 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 skillsStrong proficiency in Python, environments and dependencies tooling such as uvSolid SQL skills, data modeling knowledge, and experience with dbt or similar transformation frameworksHands-on experience with workflow orchestration (Airflow or equivalent)Experience with a modern cloud data warehouse (Snowflake or equivalent)Familiarity with CI/CD practicesKnowledge of version control with GitComfortable in Linux and/or macOS environments, writing and executing bash scriptsNice-to-have skillsExperience with Celery or other task queue systemsExperience with web crawling / scraping pipelinesExperience with Kubernetes and containerization (Docker)Experience with cloud platform (AWS or equivalent)Understanding of agile project management methodologiesExperience with observability/monitoring tools such as DatadogFamiliarity 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 serversSoft skillsYou 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.