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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Cloud Data Engineer - **Company:** Six - **Location:** Madrid, Spain - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Bash Shell, Cloud Computing, Cloud Database, Continuous Integration, Data Architecture, Information Engineering, Extract Transform Load (ETL), Identity and Access Management, Python (Programming Language), Operational Databases, Cloud Services, DataOps, Software Engineering, SQL Databases, Pulumi, Google Cloud, Apache Spark, Infrastructure as Code (IaC), Pyspark, Machine Learning Operations, Terraform, Databricks - **Published:** September 19, 2026 - **Apply:** https://www.buscojobs.com.es/cloud-data-engineer-en-madrid-ID-370501382 ## About the Role What You Bring 4+ years of practical experience building production data pipelines, data modeling and BI tools in the cloud. Experience with Lakehouse architecture, preferably Databricks, with a strong knowledge of Spark and Open Table formats (Delta and/or Iceberg). Proficiency with Python (PySpark) and SQL with a solid understanding of software development and automation concepts like CI/CD to build production data and ML pipelines (DataOps/MLOps). Basic knowledge of cloud foundation services (IAM, networking, storage...), cloud costs management (FinOps) as well as tools to manage cloud infrastructure with IaC (Terraform/OpenTofu, Pulumi, bash scripting...) on Microsoft Azure (our primary cloud service provider) and/or Amazon Web Services, Google Cloud Platform. Growth mindset and a very proactive attitude for continuous learning and development. Good presentation and communication skills. Fluency in written and spoken English. ## Description What You Will Do Be part of an international team that designs and maintains a mature cloud native data science platform, currently serving more than 14 internal analytics teams and 600+ users.Closely collaborate with key stakeholders from business data science teams and IT data engineering teams to enable them on the platform.Identify new requirements, analyze platform suitability, propose best practices and existing solutions through demos...Act as a hands-on data engineer to onboard new use cases and optimize existing ones, build production ready ETL pipelines, ML/AI use cases and reporting solutions.Implement new infrastructure components with Infrastructure as code (IaC), as well as creating templates to ensure best practices and standardization among analytics teams.What You Bring 4+ years of practical experience building production data pipelines, data modeling and BI tools in the cloud.Experience with Lakehouse architecture, preferably Databricks, with a strong knowledge of Spark and Open Table formats (Delta and/or Iceberg).Proficiency with Python (PySpark) and SQL with a solid understanding of software development and automation concepts like CI/CD to build production data and ML pipelines (DataOps/MLOps).Basic knowledge of cloud foundation services (IAM, networking, storage...), cloud costs management (FinOps) as well as tools to manage cloud infrastructure with IaC (Terraform/OpenTofu, Pulumi, bash scripting...) on Microsoft Azure (our primary cloud service provider) and/or Amazon Web Services, Google Cloud Platform.Growth mindset and a very proactive attitude for continuous learning and development.Good presentation and communication skills.Fluency in written and spoken English.If you have any questions, check out our or call Yuliya Stoyko at.For this vacancy we only accept direct applications.Diversity is important to us.Therefore, we are looking to receiving applications regardless of any personal background.What We Offer Flexible Work Models We trust our employees and offer a work environment that is well-balanced, productive and fosters success.Personal Development You will benefit from a culture of continuous learning and feedback.Your personal growth is supported through an extensive learning offering.Agile Working Methods Whether through scrum or design thinking, we solve exciting tasks together in teams. ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [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) - [Why segmenting your infrastructure into tiers makes your infrastructure design better](https://www.wearedevelopers.com/videos/1960-why-segmenting-your-infrastructure-into-tiers-makes-your-infrastructure-design-better) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence)