DATA ENGINEER

Inetum; Madrid; Hybrid; EUR 60,000 - 90,000; Full time

Job summary

Inetum in Madrid is seeking a senior Data Engineer to migrate Hadoop infrastructure to cloud-based Kubernetes, Spark on Scala, and Airflow as a service. You will design data transformations, ensure data quality, and collaborate with cross-functional teams to deliver scalable data solutions.

The role requires strong SQL/NoSQL skills, knowledge of HDFS, S3/COS, Parquet/ORC formats, and experience with CI/CD pipelines, testing, and documentation.

Qualifications

• Strong knowledge of Spark on Scala.
• Proficient in Hadoop, HDFS and SQL/NoSQL databases.
• Experience with cloud data services (COS/S3) and Parquet/ORC formats.
• Shell scripting and SDLC awareness; Agile experience.
• Ability to design data transformations and data quality processes.

Responsibilities

• Migrate the Hadoop infrastructure to cloud infrastructure on Kubernetes Engine, COS, Spark as a service, and Airflow as a service.
• Implement data transformation and quality to ensure data consistency and accuracy using Spark/Scala and SQL.
• Set up CI/CD pipelines to automate deployments, unit testing and development management.
• Write and conduct unit and validation tests to ensure accuracy and integrity of code developed.
• Automate data pipelines and streamline data ingestion with orchestrators (Airflow as a Service).
• Write technical documentation to ensure knowledge capitalization.
• Collaborate with cross-functional teams to understand data requirements and deliver solutions.

Skills

Spark

Scala

SQL

NoSQL

Hadoop

CI/CD

Agile

SDLC

Tools

Dremio

Elasticsearch

Kibana

HVault

Job description

At Inetum, a leading international digital consultancy, we empower 27,000 professionals across 27 countries to shape their careers, foster innovation, and achieve work-life balance. Proudly certified as aTop Employer Europe 2026, we’re passionate about creating positive and impactful digital solutions.

Job Description

Hybrid work mode in Madrid. This service could imply a willingness to travel occasionally within Italy.

The main responsibilities are:

• Migrate the existing Hadoop infrastructure to cloud infrastructure on Kubernetes Engine, COS, Spark as a service, and Airflow as a service.
• Implement data transformation and quality to ensure data consistency and accuracy. Utilize programming languages such as Scala and SQL and tools like Spark for data transformation and enrichment operations.
• Set up CI/CD pipelines to automate deployments, unit testing and development management.
• Write and conduct unit and validation tests to ensure accuracy and integrity of code developed.
• Automate data pipelines and streamline data ingestion through the implementation of different orchestrators and scheduling processes (Airflow as a Service mainly).
• Writing technical documentation (specifications, operational documents) to ensure knowledge capitalization.
• Collaborate with cross-functional teams to understand data requirements and deliver solutions.
• Foster a culture of continuous learning and improvement within the team.

Qualifications

Good knowledge of:

• Spark on Scala
• HDFS and structured databases (SQL)
• S3 storage/COS and parquet (and ORC) format
• Strong knowledge of SQL and NoSQL databases
• Hadoop

Full understanding of:

• Shell script
• Software Development Lifecycle (SDLC) awareness
• Agile principles and ceremonies
• Design effective prompts to leverage Gen AI tools across IT domains (e.g., development, testing, data generation, documentation) during the development stage.

Some knowledge of:

• Dremio as tool to virtualize data

Optionally/ as a plus:

• Elasticsearch and Kibana
• HVault

Additional Information

BUSINESS AND TRANSVERSAL SKILLS

• Knowledge of banking industry and processes
• Problem-Solving and Decision-Making person
• Business / IT relationship (including IT OPS)
• Ability to understand, explain and support change
• Ability to Deliver / Results driven
• Ability to collaborate / Teamwork with data squads and business teams

LANGUAGES

• Optionally Fench