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# Data Engineer (Databricks)

- **Company:** knowmad Mood
- **Location:** Madrid, Spain
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Microsoft Azure, Big Data, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Systems, Data Warehousing, Dimensional Modeling, Python (Programming Language), Meta-Data Management, Object-Oriented Software Development, Cloud Services, Standard Sql, DataOps, Data Streaming, Data Ingestion, Apache Spark, Data Lakes, Pyspark, Apache Kafka, Video Streaming, Data Pipelines, Databricks
- **Published:** November 6, 2026
- **Apply:** https://www.adzuna.es/details/5954153865

## About the Role

* More than 5 years of practical experience in Data Engineering and Big Data environments.
 * Extensive experience in Databricks and Apache Spark (PySpark).
 * Experience in designing and implementing data solutions on Microsoft Azure.
 * Solid knowledge of SQL and Python, applying clean code principles and object-oriented programming.
 * Experience working with streaming technologies such as Azure Event Hubs and Kafka.
 * Solid knowledge of dimensional modeling and Data Warehouse design principles.
 * Experience in building scalable, reliable and maintainable cloud-native data platforms.
 * Excellent communication and stakeholder management skills, with the ability to influence and guide teams without direct responsibility for project delivery.
 * Proactive, solution-oriented profile with a focus on continuous improvement.
 * Advanced English., * Experience with Databricks Lakehouse architecture.
 * Experience with Delta Lake, Unity Catalog and Databricks Workflows.
 * Experience in implementing Data Governance and DataOps practices.
 * Hold one or more Databricks certifications, such as:
 * Databricks Certified Data Engineer Associate.
 * Databricks Certified Data Engineer Professional.

## Description

* Lead the implementation of data engineering best practices using Databricks, Apache Spark and modern data platform technologies.
 * Develop reusable data ingestion frameworks and reference patterns to integrate information from corporate applications, APIs, streaming platforms and external data sources.
 * Build, maintain and optimize data pipelines, platform services and reference implementations within the data ecosystem.
 * Provide technical guidance and mentor portfolio teams in ETL/ELT processes, data engineering standards and platform capabilities.
 * Implement data governance practices, data cataloging and data quality monitoring to ensure reliable and properly documented data sets.
 * Collaborate closely with Data Architects, Data Scientists, Analysts and business areas to transform business requirements into scalable technical solutions.
 * Contribute to the continuous improvement of data platform capabilities, development standards and operational excellence practices.