Data Engineer

HN Services España; Madrid; Híbrido; EUR 45.000 - 65.000; Jornada completa

Descripción de la vacante

HN Services España is seeking a Data Engineer to join a stable international project based in Madrid. You will design and implement data pipelines, integrate data from multiple sources, and ensure data quality and security across the DataHub.

The role requires hands-on Scala/Spark work, Hadoop ecosystem experience, and collaboration in an Agile, SDLC-aware environment. A hybrid work model and flexible hours are offered.

Formación

• Experience with building data pipelines and data transformations.
• Hands-on knowledge of Hadoop ecosystem and SQL databases.
• Familiarity with cloud storage (S3/COS) and data virtualization.

Responsabilidades

• Contribute to production support and maintenance of the DataHub.
• Develop scalable data pipelines and optimize ingestion with Scala and Spark.
• Ensure data quality, security, and performance of the data platform.
• Configure CI/CD and write unit/validation tests for code changes.
• Migrate Hadoop infra to cloud-based Kubernetes and related services.

Conocimientos

Scala

Spark

SQL

Hadoop

Shell scripting

SDLC awareness

Agile

English (B2)

Herramientas

Dremio

Airflow as a Service

Kubernetes Engine

COS/S3 storage

Descripción del empleo

We are an international technology services company founded in 1983 and currently have over 2,000 employees in 5 countries: France, Spain, Romania, Portugal, and Luxembourg!

What are we looking for?

A Data Engineer to join a stable international project, based in Madrid.

Responsibilities:

• Contribute to the production support and maintenance of the DataHub, correct incidents and anomalies, resolve data-related issues, and implement functional and technical developments to ensure the stability of production processes and ensure the DataHub is available to users with minimal disruption during agreed uptime requirements.
• Modify existing code according to business requirements and continuously improve it for improved performance and maintainability.
• Ensure the performance and security of the data infrastructure and follow data engineering best practices.
• Data modeling and development of efficient data pipelines to enrich and transform large volumes of data with complex business rules, automate data pipelines, and optimize data ingestion. Design and implement scalable and secure data processing pipelines using Scala, Spark, cloud object storage, Hadoop, and COS.
• Integrate data from multiple sources and formats into the raw layer of the DataHub.
• Implement data transformation and quality to ensure data consistency and accuracy. Use programming languages such as Scala and SQL and tools such as Spark for data transformation and enrichment operations.
• Configure CI/CD pipelines to automate deployments, unit testing, and development management.
• Write and perform unit and validation tests to ensure the accuracy and integrity of the developed code.
• Implement various orchestrators and scheduling processes to automate data pipeline execution (Airflow as a Service).
• Migrate existing Hadoop infrastructure to cloud infrastructure on Kubernetes Engine, COS, Spark as a Service, and Airflow as a Service.
• Write technical documentation (specifications, operational documents) to ensure knowledge capitalization.

Requirements:

• Spark on Scala
• HDFS and structured databases (SQL)
• Hadoop
• S3 storage/COS
• Shell script
• Software Development Lifecycle (SDLC) awareness
• Agile principles and ceremonies
• Dremio as tool to virtualize data

Optionally/ as a plus

• Elasticsearch and Kibana
• HVault
• English B2 or higher.

Work Model:

• Hibrid.
• Flexible hours, Monday to Friday.

We offer:

Career plan tailored to employee preferences

Progression within the company

Flexible working hours

Would you like to join our team?