Senior Data Engineer

Overview: We are seeking a highly skilled and experienced Senior Data Engineer with a minimum of 5 years working with Databricks and Lakehouse architecture to join our team in the consumer finance industry. The successful candidate will play a critical role in mapping requirements, designing, implementing, and maintaining scalable data solutions, and will ensure seamless integration and operation of CI/CD pipelines. Key Responsibilities: Design, develop, and optimize robust data architectures using Databricks and Lakehouse principles to support large-scale and complex data analytics needs. Implement and maintain CI/CD pipelines to ensure continuous integration and delivery of data solutions, ensuring data quality and operational efficiency. Collaborate with cross-functional teams (ideally Finance) to understand data requirements, map data through distributed systems, and translate these into technical solutions that align with business objectives. Manage and optimize data storage and retrieval systems to ensure performance and cost-effectiveness. Develop, maintain, and document ETL/ELT processes for data ingestion, transformation, and loading using industry best practices. Ensure data security and compliance, particularly within the context of financial data, adhering to relevant regulations and standards. Troubleshoot and resolve any data-related issues, ensuring high availability and reliability of data systems. Evaluate and incorporate new technologies and tools to improve data engineering practices and productivity. Mentor junior data engineers and provide technical guidance to the wider team. Contribute to the strategic planning of data architecture and infrastructure. Required Qualifications and Experience: Bachelor’s degree in Computer Science, Information Technology, or a related field. A Master’s degree is a plus. Minimum of 5 years of professional experience as a Data Engineer or in a similar role within the finance industry, demonstrating experience of working with consumer finance data models. Proficient in using Databricks for data engineering and analytics. Strong experience with Lakehouse architecture and its optimization. Highly proficient in programming languages such as Python Demonstrable expertise in implementing and managing CI/CD pipelines for data solutions Solid experience with cloud platforms (e.g., AWS, Azure, or GCP), and their data services. Deep understanding of data warehousing concepts and technologies (e.g., Snowflake, Redshift). Strong knowledge of ETL/ELT processes and tools. Solid experience of utilising PowerBI or similar visualisation tools Experience working with big data technologies and frameworks (e.g., Spark) Excellent problem-solving skills and a proactive approach to data engineering challenges. Strong communication skills with the ability to articulate complex technical concepts to non-technical stakeholders. Desirable Skills: Certifications in Databricks or cloud technologies. Experience with machine learning pipelines and model deployment. Knowledge of regulatory requirements in the finance industry, such as GDPR or PCI-DSS. Experience with agile development methodologies, such as Scrum or Kanban.

Location: Madrid, Community of Madrid, ES

Posted Date: 11/16/2025