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# Data Engineer

- **Company:** Sowelo Consulting
- **Location:** Spain (Remote available)
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Microsoft Azure, Software Quality, Data as a Services, Information Engineering, Extract Transform Load (ETL), Data Transformation, Data Systems, Python (Programming Language), Software Maintenance, SQL Databases, Build Management, Information Technology, Data Pipelines, Databricks
- **Published:** November 12, 2026
- **Apply:** http://soweloconsulting.theresumator.com/apply/jobs/details/N05vz0U9vV

## About the Role

* 4+ years of hands-on experience in data engineering, data transformation, or analytics engineering.
 * Strong proficiency in Python and SQL (familiarity with Scala is a nice-to-have).
 * Practical experience designing and maintaining data pipelines within the Databricks ecosystem.
 * Working knowledge of public cloud environments (Azure, AWS, or GCP), specifically compute, storage, and data services.
 * Higher education in Computer Science, STEM, or equivalent real-world technical experience.
 * Strong focus on code quality, testing, and writing clean, maintainable software.
 * Excellent communication skills tailored for effective remote-first collaboration.

## Description

Our client is an innovative AI and data solutions consultancy and we are seeking a motivated Data Engineer to join their growing team. In this role, you will design, develop, and maintain modern data solutions using Databricks, helping clients and internal teams process, transform, and analyze data effectively. You will work on reliable end-to-end data pipelines in a collaborative environment, gaining hands-on experience with modern cloud architectures.

This is a 100% fully remote role and it involves working with customers in US Eastern time zone.

Your Tasks Will Include:

 * Collaborate with cross-functional teams to design and build scalable data pipelines and workflows in Databricks.
 * Develop ETL/ELT processes using Databricks, Python, and SQL to ingest, transform, and prepare data.
 * Optimize data workflows for higher performance, reliability, and cost-efficiency within cloud environments.
 * Support the creation and maintenance of data models, tables, and integrations on cloud platforms (Azure, AWS, or similar).
 * Partner with data analysts and scientists to deliver clean, accessible data for analytics and reporting.
 * Monitor pipelines, troubleshoot technical issues, and contribute to internal documentation and best practices.
 * Stay curious about emerging Databricks features and industry trends to drive continuous improvement.