Data Platform Engineer — PySpark, Lakehouse & Databricks

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

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.