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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Foundever - **Location:** Madrid, Spain - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Computer Programming, Data Validation, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Systems, Data Visualization, Data Warehousing, Document-Oriented Databases, Apache Hadoop, Monitoring of Systems, Python (Programming Language), Machine Learning, NoSQL, SQL Databases, Data Storage Technologies, Apache Spark, Data Lakes, Information Technology, AWS Glue, Software Version Control, Data Pipelines - **Published:** September 24, 2026 - **Apply:** https://www.adzuna.es/contact-us.html ## About the Role This role requires strong proficiency in data modelling, database management, and programming skills in Python and SQL. You should have experience with big data technologies, ETL processes, data warehousing, and cloud platforms. Additionally, expertise in implementing data security measures and maintaining data systems in regulated environments is essential., Minimum of 7 years plus experience in data engineering. Track record of deploying and maintaining complex data systems at an enterprise level within regulated environments. Expertise in implementing robust data security measures, access controls, and monitoring systems. Skills / Abilities / Knowledge Proficiency in data modeling and database management. Strong programming skills in Python and SQL. Knowledge of big data technologies like Hadoop, Spark, and NoSQL databases. Deep experience with ETL processes and data pipeline development. Strong understanding of data warehousing concepts and best practices. Experience with cloud platforms such as AWS and Azure. Excellent problem-solving skills and attention to detail. Ability to collaborate effectively with cross-functional teams. Strong communication skills, both written and verbal. Ability to keep abreast of industry trends and emerging technologies in data engineering., Bachelors in Computer Science or Engineering Languages Excellent command of English. French and Spanish language skills are a bonus. ## Description We are looking for a Senior QA Engineer to join our globally distributed team of AI evangelists to build reliable, scalable and secure GenAI-powered products. You will help us shape the future of CX by driving quality initiatives, strengthening QA processes and ensuring we deliver high-quality and stable products to our users., We are looking for an experienced Senior Data Engineer to join our AI team. You will be responsible for designing and optimizing complex data storage solutions, developing and maintaining efficient data pipelines, and ensuring data quality and integrity. Working closely with data analysts, machine learning engineers, and software engineers, you will deliver relevant datasets or data APIs for downstream applications., Design and optimize complex data storage solutions, including data warehouses and data lakes. Develop, automate, and maintain data pipelines for efficient and scalable ETL processes. Ensure data quality and integrity through data validation, cleansing, and error handling. Collaborate with data analysts, machine learning engineers, and software engineers to deliver relevant datasets or data APIs for downstream applications. Implement data security measures and access controls to protect sensitive information. Monitor data infrastructure for performance and reliability, addressing issues promptly. Stay abreast of industry trends and emerging technologies in data engineering. Document data pipelines, processes, and best practices for knowledge sharing. Lead data governance and compliance efforts to meet regulatory requirements. Collaborate with cross-functional teams to drive data-driven decision-making within the organization., Programming languages and tools: Python, SQL. Big data technologies: Hadoop, Spark, NoSQL databases. ETL and data pipeline tools: AWS Glue, Airflow. Cloud platforms: AWS, Azure. Data visualization tools and data modeling software. Version control systems and collaborative development platforms. 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