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# Data Engineer

- **Company:** Número De
- **Location:** Spain (Remote available)
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Application Frameworks, BigQuery, Data Validation, Information Engineering, Extract Transform Load (ETL), Data Systems, Performance Tuning, Software Engineering, SQL Databases, Data Processing, Google Cloud, Sql Optimization, Data Lakes, Pyspark, Software Version Control, Data Pipelines, Databricks
- **Published:** September 29, 2026
- **Apply:** https://www.adzuna.es/details/5902562780

## About the Role

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!, 5+ years of strong hands-on experience with Databricks and PySpark.

 - Advanced SQL and data-processing skills.
 - Hands-on experience with GCP, particularly BigQuery.
 - Experience with Delta Lake and modern data lake/lakehouse architectures.
 - Strong understanding of ETL/ELT, data pipeline design, performance optimization, and data quality.
 - Experience building reliable, scalable, production-grade data solutions.
 - Strong analytical and troubleshooting skills.
 - Understanding of software engineering practices, including testing, version control, deployment, monitoring, and production support.
 - Upper-intermediate English level., Experience developing or integrating AI/agentic workflows, AI agents, or workflow automation solutions.
 - Experience applying AI to automate data engineering, validation, troubleshooting, or operational processes.
 - Familiarity with orchestration and automation frameworks.
 - Experience developing reusable data engineering frameworks and platform components.
 - Exposure to productionizing AI-enabled solutions with appropriate validation, monitoring, and human oversight.

## Description

We are looking for a Data Engineer with strong Databricks and GCP experience to develop scalable ETL/ELT pipelines and productionize agentic workflows for data engineering automation., Design, develop, and optimize scalable ETL/ELT data pipelines using Databricks, PySpark, and SQL.

 - Build and operationalize agentic workflows to automate data engineering and operational processes such as data validation, issue identification, troubleshooting, and workflow execution.
 - Integrate agentic capabilities with existing Databricks, GCP, BigQuery, and Delta Lake environments.
 - Develop data pipelines and processing solutions to support new business requirements and datasets.
 - Build reusable frameworks and components that can be leveraged across multiple data engineering and business use cases.
 - Implement data quality checks, monitoring, validation, exception handling, and production controls.
 - Optimize PySpark and SQL workloads for performance, reliability, and scalability.
 - Support testing, deployment, productionization, and ongoing enhancement of data and agentic solutions.
 - Troubleshoot complex data and production issues and implement sustainable solutions.
 - Collaborate with business, data engineering, and platform teams to identify further automation opportunities.