Data Engineer

Launchmetrics; Paris; Hybride; EUR 90 000 - 120 000; Plein temps

Avantages offerts par ce poste

Learning & development allowance

Benefits package tailored to location

Flexible working arrangements

Remote-friendly with hubs

Résumé du poste

Launchmetrics in Paris is seeking a Data Engineer to design and build batch and near-real-time data pipelines on a Databricks-based Lakehouse, enabling richer data products used across the organization.

You will own schema design, enrichment workflows, and collaborate with product and QA to ensure reliability and cost efficiency in a fast-paced SaaS environment. Fluent English required; remote-friendly with hub access across markets.

Qualifications

• Engineer degree or Master in Computer Science with 3+ years in SaaS full‑stack development
• Strong Python and PySpark experience with distributed data processing at scale
• Experience with Lakehouse architecture (Databricks, Delta Lake or equivalent)
• Familiarity with Bronze/Silver/Gold medallion patterns in data design
• Ability to reason about schema evolution, partitioning and pipeline reliability
• Excellent English communication and collaboration skills

Responsabilités

• Design and build data pipelines (batch and near-real-time) using PySpark and Databricks
• Architect efficient Delta Lake table schemas and enrichment workflows
• Collaborate with product, QA and other data engineers to ensure reliable pipelines
• Own code quality with structured PySpark jobs and unit tests
• Improve pipeline reliability and cost efficiency (scheduling, retries, concurrency)
• Participate in cross-pod initiatives across the data platform

Connaissances

Python

PySpark

Distributed data processing

SQL

English fluency

Data concepts

Problem solving

Formation

Bachelor’s or Master’s in Computer Science

Outils

Databricks

Delta Lake

GitHub

Jira

Serverless

Claude Code

Description du poste

About Launchmetrics

Launchmetrics is the leading Brand Performance Cloud used by Fashion, Lifestyle and Beauty (FLB) executives to make smarter decisions around their branding efforts.

About Launchmetrics

Launchmetrics is the leading Brand Performance Cloud used by Fashion, Lifestyle and Beauty (FLB) executives to make smarter decisions around their branding efforts.

With over a decade of industry expertise, we have helped more than 1,200 customers create inspiring, impactful and measurable experiences.

Founded in NYC and with operating headquarters in Paris, we have employees in ten markets worldwide and offer support in five languages. We have been the trusted brand performance technology to brands worldwide such as Dior, Fendi, Shiseido, NET-A-PORTER and Adidas as well as industry partners like IMG, the Council of Fashion Designers of America, the British Fashion Council, and Camera Nazionale Della Moda Italiana.

The Team & the Pods organization

We are a team of passionate engineers distributed across the world, always eager to learn new things. We are building state-of-the‑art modern applications and scale it on the cloud. We innovate to solve customers problems, focusing on high‑performance implementations without neglecting the user experience.

We recently moved our Product and Tech teams to a pod model:

• A pod is a small group, 1 to 4 people, that owns a single mission end to end: from scoping and building through cleaning, enablement and watching adoption. Pods form around a mission and dissolve when it's done. Everyone is a pod owner, from the most junior person to the most senior, because ownership is the point.
• Your domain is your product‑area home, the part of our software suite you know best. Pods change with every mission; your craft and your domain don't.

The role

The Data Platform and Data Enrichment teams are in charge of making our unified database accessible, usable, enrichable and reliable for all our teams internally.

The team owns the Lakehouse that powers Launchmetrics' data products — a Databricks‑based platform built on Delta Lake, S3, and following a Bronze/Silver/Gold medallion architecture. This layer stores, enriches, and serves the media intelligence data behind Discover (our client‑facing platform), Genie (internal tooling), and Delta Sharing. You'll work on a batch‑first system that simulates real‑time behavior using primitives like Change Data Feed, S3 event triggers, serverless compute, and liquid clustering.

This role plays a key part in our Tech & Product strategy, directly supporting company‑wide objectives around customer retention, data trust, and the development of new AI‑based insights.

What you'll do

• Design and build data pipelines (batch and near‑real‑time) using PySpark and Databricks, across the Bronze/Silver/Gold medallion layers
• Architect efficient Delta Lake table schemas — partitioning/liquid clustering strategy, schema evolution handling, and enrichment workflows
• Work closely with product, QA, and other data engineers to translate enrichment and search requirements into reliable pipelines
• Own code quality: structured PySpark jobs, unit tests (pytest), and adherence to team conventions
• Continuously improve pipeline reliability and cost efficiency (OPTIMIZE scheduling, retry/backoff logic, concurrency handling)
• Participate in cross‑pod initiatives across the data platform

Technical Stack

• Languages: Python, PySpark, Typescript
• Data Platform: Databricks, Delta Lake, Delta Sharing
• Storage: AWS S3, MySQL
• Cloud: AWS (S3, Kinesis, Lambda, SQS, ECS, Step Functions, …)
• Tools: Jira, Databricks Asset Bundles, Serverless, Claude Code
• Versioning: Git, GitHub
• CI/CD: GitHub Actions
• Testing: pytest, Jest

What we're looking for

• Engineer Degree or Master Degree in Computer Science and 3+ years of relevant work experience in full‑stack development in a SaaS environment
• Strong Python and PySpark experience; comfort with distributed data processing at scale
• Experience with a Lakehouse architecture (Databricks, Delta Lake, or comparable — e.g. Spark on EMR/Glue)
• Familiarity with medallion architecture patterns (Bronze/Silver/Gold) or similar layered data design
• Ability to reason about schema evolution, partitioning/clustering strategy, and pipeline reliability (retries, idempotency)
• Ability to traverse logical sequences of either procedural or object‑oriented code, abstracted or static - and understand it entirely
• Bright, energetic, highly motivated self‑starter with experience in a fast‑paced, results‑oriented organization
• Ability to adapt, estimate workload, break down a task into logical steps, solve problems, self‑improve and suggest new ways of improvement
• Last, but definitely not least: you speak, read, and write English fluently

How we hire

• Intro call with Talent Acquisition, to get to know each other (30 min).
• Meet & Greet with VP Software Development.
• Technical Interview, a live interview with a couple of Software Engineers.
• Team fit with the engineers and peers you'd build alongside.

Why you'll love it here

We're a company that puts people first, with a relaxed but genuinely dynamic atmosphere and a team of motivated, curious people who like their work. Autonomy is real here: pods make local decisions and own their outcomes, which means you'll see your fingerprints on the product quickly.

You’ll get a learning and development allowance, a benefits package tailored to your location, flexible working arrangements with support to set up your home office, and the room to grow along whichever path fits you. We're remote‑friendly, with hubs across our twelve markets.

OUR COMMITMENT

Launchmetrics is proud to be an Equal Opportunity Employer building a diverse and inclusive workforce. If there is anything extra we can do to help you feel at ease during your interview process, please let the PeopleOps team member you’ll be meeting with know.