We are looking for a talented Data Engineer to help shape the next generation of AI-driven financial crime detection solutions. If you have strong data engineering expertise hands-on experience building and optimizing large-scale data pipelines and a passion for solving complex real-world challenges this could be the perfect opportunity for you. In this role you will design and develop the data foundations that power advanced money laundering detection solutions for leading financial institutions worldwide.

Responsibilities Develop implement and maintain production-grade data pipelines based on data science requirements. Design and build scalable data flows for specific business use cases that can be integrated into the product. Build and maintain machine learning data pipelines.

Create tools and frameworks that support data scientists and analytics teams in developing and optimizing innovative solutions. Collaborate closely with Product RD Data and Analytics teams to enhance system functionality and performance. Train customer data scientists and engineers on maintaining and enhancing data pipelines within the platform.

Travel domestically and internationally to support customers when required. Build and manage strong technical relationships with customers and partners.

Requirements 2+ years of hands-on experience with Apache Spark (required). Strong experience with SQL.

Experience using version control systems particularly Git.



Hands-on experience with the Apache Hadoop ecosystem including Hive Impala Hue HDFS and Sqoop.

Experience with Python (Pandas).

Experience with PySpark Scala Java or R. Proven experience in data transformation validation cleansing and machine learning feature engineering. Bachelors degree or higher in Computer Science Statistics Informatics Information Systems Engineering or another quantitative field.

Experience working with and optimizing large-scale data pipelines architectures and datasets. Strong analytical skills and experience working with structured and semi-structured data.

Experience building processes that support data transformation metadata management dependency management and workload optimization. Ability to perform root cause analysis on data and processes to answer business questions and identify improvement opportunities. Strong customer-facing and cross-functional collaboration skills. Fluent in English preferred but not mandatory Spanish Advantages Experience working with Linux.

Experience building machine learning pipelines. Knowledge of Elasticsearch.

Experience with Zeppelin and/or Jupyter. Familiarity with workflow orchestration tools such as Jenkins or Apache Airflow.

Experience with microservices and containerization technologies including Docker and Kubernetes. What we can offer Additional 20 days of paid leave Professional and career benefits Top-quality work environment Online courses Online sports activities Team Buildings and Christmas Parties

📌 Data Engineer (Madrid)
🏢 Matrix Eastern Europe
📍 Madrid