Data Engineer

ThetaRay; Madrid; Presencial; EUR 70.000 - 100.000; Jornada completa

Descripción de la vacante

ThetaRay is seeking a Data Engineer in Madrid to transform data pipelines and enable real-time detection for financial crime. You will contribute to building data flows and ML pipelines powering our AI-driven products for global banks and fintechs.

Requirements include Spark, Hadoop ecosystem, Python, SQL, and experience with data transformations and feature engineering. Fluency in English and Spanish is essential; some travel to customer sites is required.

Formación

• 2+ years of hands-on experience with Apache Spark, data pipelines, and big data processing.
• Strong SQL and data transformation skills, with experience in Hadoop ecosystem tools.
• Proficiency with Python (Pandas) and at least one JVM language (PySpark/Scala/Java/R).
• Experience building ML data pipelines and feature engineering for detection or analytics tasks.
• BSc or higher in a quantitative field; able to work with English and Spanish.

Responsabilidades

• Implement and maintain data pipeline flows in production within the ThetaRay system based on the data scientist’s design.
• Design and implement data flows for specific use cases to power ThetaRay products.
• Build a Machine Learning data pipeline and data tools for analytics and scientists.
• Collaborate with product, R&D, data, and analytics teams to enhance system functionality.
• Train customer data scientists and engineers to maintain data pipelines; travel as needed.

Conocimientos

Apache Spark

SQL

Git

Hadoop

Hive

Impala

Hue

HDFS

Sqoop

Python

Pandas

PySpark

Scala

Java

R

Data transformation

ML feature engineering

English

Spanish

Educación

BSc in Computer Science / Statistics / Informatics / Engineering

Herramientas

Apache Airflow

Elasticsearch

Zeppelin/Jupyter

Docker

Kubernetes

Linux

Jenkins

Descripción del empleo

At ThetaRay, our purpose is to make the world a safer place by protecting the integrity of the global financial system.

We do this by putting AI at the core of both our technology and our way of working. Our AI-driven solutions help banks and fintech companies worldwide detect and stop serious financial crime, from human trafficking and terrorist financing to sophisticated money laundering, while advanced technology, automation, and AI-driven tools help our teams collaborate smarter, move faster, and continuously improve how we build, deliver, and innovate.

About the role:

We are looking for a Data Engineer to turn expertise, initiative, and bold thinking into real impact on the next generation of AI-driven financial crime detection.

If you combine strong data engineering capabilities with hands-on experience in building and optimizing data pipelines and transformations at scale, and if you are motivated by designing the data flows that power real-world money laundering detection for global financial institutions, ThetaRay could be your next challenge.

Responsibilities:

• Implement and maintain data pipeline flows in production within the ThetaRay system based on the data scientist’s design
• Design and implement solution-based data flows for specific use cases, enabling the applicability of implementations within the ThetaRay product
• Building a Machine Learning data pipeline
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader
• Work with product, R&D, data, and analytics experts to strive for greater functionality in our systems
• Train customer data scientists and engineers to maintain and amend data pipelines within the product
• Travel to customer locations both domestically and abroad
• Build and manage technical relationships with customers and partners

Requirements:

• 2+ years of Hands-on experience working with Apache Spark - must
• Hands-on experience with SQL
• Hands-on experience with version-control tools such as GIT
• Hands-on experience with Apache Hadoop Ecosystem including Hive, Impala, Hue, HDFS, Sqoop etc..
• Experience with Python (Pandas)
• Experience with PySpark/Scala/Java/R
• Hands-on experience with data transformation, validations, cleansing, and ML feature engineering
• BSc degree or higher in Computer Science, Statistics, Informatics, Information Systems, Engineering, or another quantitative field
• Experience working with and optimizing big data pipelines, architectures, and data sets - an advantage
• Strong analytic skills related to working with structured and semi-structured datasets
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• Business-oriented and able to work with external customers and cross-functional teams
• Fluent in English & Spanish both written and spoken

Nice to have

• Experience with Linux
• Experience in building Machine Learning pipeline
• Experience with Elasticsearch
• Experience with Zeppelin/Jupyter
• Experience with workflow automation platforms such as Jenkins or Apache Airflow
• Experience with Microservices architecture components, including Docker and Kubernetes.