Experteer Overview

Asegúrese de enviar su solicitud rápidamente para maximizar sus posibilidades de ser considerado para una entrevista. Lea la descripción completa del puesto a continuación.

In this role you will design and build batch and near-real-time data pipelines on a Databricks-based Lakehouse to enable reliable enrichment and AI-driven insights. You will work within the Data Platform and Data Enrichment team, contributing to data trust and customer-focused data products that power Discover and internal tooling. The role combines hands-on engineering with cross-pod collaboration to scale data infrastructure and improve pipeline reliability.

You will be part of a mission-driven, pod-based culture that values ownership and continuous learning. This is a chance to shape scalable data foundations and enable impactful analytics for a global brand ecosystem.

Compensaciones / Incentivos

- Design and implement batch and near-real-time data pipelines using PySpark and Databricks across Bronze/Silver/Gold layers
- Architect efficient Delta Lake table schemas, including partitioning, liquid clustering, schema evolution, and enrichment workflows
- Collaborate with product, QA,



and other data engineers to translate enrichment and search requirements into reliable pipelines
- Own code quality with structured PySpark jobs, unit tests (pytest), and team conventions
- Improve pipeline reliability and cost efficiency through scheduling optimization, retry logic, and concurrency management
- Contribute to cross-pod initiatives within the data platform

Responsabilidades

- 3+ years of relevant work experience in a SaaS environment with distributed data processing
- Strong Python and PySpark experience
- Hands-on experience with Lakehouse architectures (Databricks, Delta Lake, xugodme or equivalents)
- Familiarity with Bronze/Silver/Gold data design patterns and schema evolution
- Ability to reason about code, understand complex logic, and work with both procedural and object-oriented code
- Self-motivated, adaptable, and able to thrive in a fast-paced, results-oriented setting
- Fluent English

Requisitos principales

- learning and development allowance
- flexible working arrangements
- remote-friendly with home office support
- location-based benefits
- opportunity for growth
- pod autonomy

📌 Data Engineer (Madrid)
🏢 Launchmetrics
📍 Madrid