Madrid - Data Engineer

About the role

New Role: Data Engineer, Data Analytics Team

This page outlines the position for a Data Engineer within our client's Data Analytics Team in Madrid. The role focuses on constructing and maintaining the data infrastructure that supports critical investment decisions.

Our Culture

We seek individuals who demonstrate exceptional talent and superior communication abilities. Collaboration drives our success, both internally and with clients. We perform our best work collectively, engaging directly with business users. Curiosity is a core value we actively embrace and reward. We select people who are positive, passionate, and possess proven problem-solving capabilities. They work efficiently to resolve complex challenges and identify significant opportunities. Team members must take ownership and be trusted to deliver results, going the extra mile consistently. A high degree of motivation and a strong desire to learn are essential attributes.

Responsibilities

The primary role involves building data pipelines that import information from external vendors and sell-side partners into our central data platform. We require development, testing, and ongoing maintenance of this platform to guarantee its availability, reliability, and data integrity.

Key expectations include specific duties. Data Pipeline Development requires designing and constructing sophisticated pipelines to ensure seamless data flow into our systems. Platform Development and Testing involves contributing to continuous enhancements to meet evolving business needs. Regular system testing is necessary to confirm effectiveness and perform troubleshooting. Platform Maintenance and Data Reliability focuses on keeping the platform operational to provide uninterrupted access to vital data points. Continuous verification of data quality and integrity is mandatory for the investment process. Continuous Improvement and Collaboration centers on working with internal stakeholders to streamline data accessibility. Driving innovation through advanced analytics technologies is a core function.

What Makes a Great Candidate

Candidates must bring 3-6 years of specific experience as a data engineer or related finance roles. A degree in Computer Science or a related field is required, with a minimum score of 7.0 and a strong academic background. Hedge fund experience is essential from the first day. Expertise in designing and building data pipelines is non-negotiable. Proficiency in SQL, Python, AWS, and other data management technologies is required. Familiarity with version control systems like Git and orchestration tools like Airflow is mandatory. The ability to test and troubleshoot data platforms reliably, with a track record of improving data quality, is expected. Excellent communication skills and effectiveness in a team-based environment are crucial. Candidates should be self-starters, detail-oriented, and open to learning new technologies.

Why Join Us

New team members make an impact from their first day. We empower people to use and extend their skill sets extensively. The work involves a wide variety of projects alongside exceptionally talented individuals. Projects often correlate with world events and trends. Team members deliver demonstrable business value by working hand-in-hand with customers. Learning from industry experts provides insights into financial markets and global economies.

Key Facts

Location is Madrid. The engagement is Full time. The compensation range is 70,000 - 80,000 EUR.

Day-to-Day Activities

You will design intake steps for messy vendor feeds to create one unified platform. Building core pipelines that connect sell-side partners to analytics layers occurs daily. Reviewing data quality rules ensures reliability stays high across critical datasets. Shipping dashboards that business users trust happens regularly here. Partnering with clients aligns tools with their workflow and immediate goals. Testing new AWS features before wide rollout protects stable environments. Tracing errors through logs fixes pipeline issues before users notice. Documenting setups allows replacements to understand and extend systems easily.

Requirements

You must hold 3-6 years of experience as a data engineer in finance contexts with real results. A Computer Science degree must appear with a minimum 7.0 score and strong earlier grades. Hedge fund background is mandatory from day one. SQL, Python, and AWS skills are essential for daily tasks and quick fixes. Using Git for version control and Airflow for orchestration must feel routine. Thorough testing of platforms and tracking improvements in reliability metrics are required.