Data Engineer

Ryanair - Europe's Favourite Airline; Madrid; Presencial; EUR 55.000 - 75.000; Jornada completa

Descripción de la vacante

Ryanair Labs, the technology hub of Europe’s largest airline group, is recruiting a Data Engineer to expand data capabilities across its 800 aircraft and 300 million guests vision. You will design ELT pipelines, maintain data lakes in AWS, and collaborate with Data Science to enable scalable model deployment in a fast-paced, agile environment.

Key responsibilities include building batch and real-time processing with Kafka and AWS services, implementing monitoring, and delivering high-quality

Formación

• 3+ years of data engineering or related data processing experience.
• Experience with varied data formats (JSON, CSV, Parquet, APIs).
• Hands-on data modeling in Big Data platforms (Databricks, Glue, Snowflake).
• Familiarity with event-driven architectures and AWS.
• Experience building monitoring, alerting, and debugging for data pipelines.

Responsabilidades

• Design and develop automated ELT processes with Spark, Airflow, DBT, Python, and Databricks.
• Build and maintain batch and real-time data processing using Kafka and AWS services.
• Maintain AWS data lake and Databricks models for efficient consumption.
• Implement monitoring and observability for data pipelines.
• Collaborate with teams to collect and process business data needs.
• Support Data Science with scalable environments for models.
• Create and maintain CICD pipelines for deployments.
• Manage deployed infrastructure and adherence to engineering standards.
• Deliver work on time and align priorities with team goals.

Conocimientos

Data engineering experience

Data formats proficiency

SQL and performance tuning

Python coding

Big data concepts

Herramientas

Spark

Apache Airflow

DBT

Databricks

Python

Kafka

AWS

S3

EC2

VPC

IAM

Descripción del empleo

Ryanair Labs are currently recruiting for a Data Engineer to join Europe’s Largest Airline Group!

This is a very exciting time to join Ryanair as we look to expand our operation to 800 aircraft and 300 million guests within the next 10 years.

Ryanair Labs is the technology brand of Ryanair. Labs is a state of-the-art digital & IT innovation hub creating Europe’s Leading Travel Experience for our customers.

Key Responsibilities

• Design and develop automated ELT processes ensuring a high level of data quality and reliability, using tools such as Spark, Apache Airflow, DBT, Python, Databricks, etc.


• Build and maintain batch and real-time data processing using Apache Kafka and AWS services like SNS, SQS, and Kinesis, supporting microservice architectures.


• Maintain the data lake in AWS and Databricks, building well-governed, query-oriented data models for efficient consumption.


• Implement monitoring and observability for the pipelines you work on.


• Collaborate cross-functionally, assisting other teams in identifying, collecting, and processing valuable information for diverse business use cases.


• Support the Data Science team by helping ensure stable, scalable environments for model deployment and experimentation.


• Build and maintain CICD pipelines, following best practices for automatic deployment and consistency.


• Help administer and maintain deployed infrastructure.


• Follow and contribute to engineering standards and best practices across the Data Engineering team.


• Deliver work on time, managing your own priorities in line with team commitments.

Skills And Experience Required

• 3+ years in data engineering or related data processing roles.


• Strong experience working with varied data formats and sources (JSON, CSV, Parquet, APIs, multiple DB engines).


• Hands-on experience with data modelling in Big Data platforms (e.g. Databricks, Glue, Snowflake).


• Familiarity with event-driven architectures and AWS.


• At least 2 years of hands-on experience with AWS, especially:


• Core: IAM, S3, EC2, VPC


• Data Services: EMR, Lambda, Batch, SNS, SQS, DynamoDB, Glue, Athena


• Ability to set up and maintain monitoring, alerting, and debugging solutions for your pipelines.


• Experience collaborating with Data Science teams to support production-grade pipelines.

Knowledge

• Solid understanding of computing systems (OS, memory, networks, etc.).


• Proficient in data analysis and interpretation, with a good grasp of statistics and data quality methods.


• Strong SQL and performance tuning skills.


• Good knowledge of Big Data technologies, Spark, and object storage systems.


• Proficiency in Python (and optionally Scala), with strong coding and testing practices.


• Familiarity with Docker; Kubernetes experience is a plus.


• Airflow (or similar) for orchestration.


• Good understanding of IaaC and CICD principles.


• Dashboard and storytelling experience for data visualization.

Other

• Strong communication skills.


• Proactive mindset and collaborative team spirit.


• Comfortable working within an agile team setup.