> Markdown version of [/jobs/ext/1999411-data-engineer](https://www.wearedevelopers.com/jobs/ext/1999411-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Engineer

- **Company:** Launchmetrics
- **Location:** Madrid, Spain
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Unit Testing, Software as a Service, Software Quality, Data Architecture, Data Cleansing, Data Infrastructure, Distributed Computing Environment, Python (Programming Language), Object-Oriented Software Development, Pytest, Data Lakes, Pyspark, Data Analytics, Data Pipelines, Databricks
- **Published:** August 9, 2026
- **Apply:** https://www.buscojobs.com.es/data-engineer-en-madrid-ID-366703044

## About the Role

This is a chance to shape scalable data foundations and enable impactful analytics for a global brand ecosystem.Compensaciones / Beneficios* 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 platformResponsabilidades* 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, xqbhyrx 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 EnglishRequisitos principales* learning and development allowance* flexible working arrangements* remote-friendly with home office support* location-based benefits* opportunity for growth* pod autonomy

## Description

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 / Beneficios* 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 platformResponsabilidades* 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, xqbhyrx 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 EnglishRequisitos principales* learning and development allowance* flexible working arrangements* remote-friendly with home office support* location-based benefits* opportunity for growth* pod autonomy


## Related Videos

- [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning)
- [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data)
- [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt)
- [pytest: Simple, rapid and fun testing with Python](https://www.wearedevelopers.com/videos/213-pytest-simple-rapid-and-fun-testing-with-python)
- [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail)
- [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works)

## Related Articles

- [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk)
- [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)
- [Spanish Business Culture and Etiquette](https://www.wearedevelopers.com/magazine/353-spanish-business-culture-and-etiquette)
- [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs)
- [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)
- [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)