Description
Job Summary:
We are seeking a Data Engineer with experience in Big Data ecosystems to participate in an international project migrating Hadoop infrastructure to cloud environments based on Kubernetes.
Key Highlights:
1. International Big Data environment project
2. Participation in data platform modernization projects
3. Modern technology environment
Data Engineer
We are seeking a Data Engineer with experience in Big Data ecosystems to participate in an international project focused on migrating Hadoop infrastructure to Kubernetes-based cloud environments.
You will join a data engineering team responsible for designing, developing, and automating data pipelines, working with technologies such as Spark, Scala, Airflow, and CI/CD tools within an agile environment.
Responsibilities
Migrate Hadoop infrastructure to cloud using Kubernetes Engine, COS, Spark as a Service, and Airflow as a Service.
Develop data transformation and data quality processes to ensure consistency and accuracy.
Implement data pipelines using Scala, SQL, and Apache Spark.
Automate processes using Airflow and orchestration tools.
Create and maintain CI/CD pipelines for automated deployment and testing.
Develop unit tests and validate data processes.
Prepare technical and operational documentation.
Collaborate with business and technology teams to design scalable data solutions.
Technical Requirements
Experience with Apache Spark and Scala
Experience with Hadoop ecosystem
Knowledge of SQL and NoSQL databases
Experience with Apache Airflow
Experience with HDFS
Experience with CI/CD (GitLab, Jenkins or similar)
Knowledge of S3 / COS Storage
Experience working with Parquet and ORC
Additional Desirable Skills
Kubernetes / containerization
Oozie
Shell scripting
Dremio
Elasticsearch / Kibana
Kafka or streaming processing
What We Offer
International Big Data environment project
Hybrid work model in Madrid (1 day onsite)
Participation in data platform modernization projects
Modern technology environment
Spark, Scala, SQL, NoSQL, CI/CD, S3, COS Storage