Requirements: English
Company: ITDS
Region: Krakw , Lesser Poland Voivodeship
Join us, and transform massive data into meaningful insights!
Krakw - based opportunity with hybrid work model (2 days/week in the office).
As a Hadoop Data Engineer, you will be working for our client, a globally recognized financial institution driving innovation in digital infrastructure and data intelligence. You will be contributing to the development and deployment of large-scale, cloud-based data solutions that support business-critical analytics and data processing. Working within a hybrid model and cross-functional teams, you will play a key role in transforming traditional data platforms into scalable, automated, and high-performance environments on a modern tech stack including GCP, Hadoop, Spark, and Scala.
You''re ideal for this role if you have:
- 5+ years of hands-on experience with Hadoop ecosystem (HDFS, Hive)
- Strong programming skills in Scala and experience with Apache Spark
- Proven experience working with Google Cloud Platform services
- Proficiency in building and scheduling workflows using Apache Airflow
- Expertise in writing complex SQL queries and data transformation logic
- Familiarity with DevOps tools such as Jenkins, Git, and GitHub
- Understanding of distributed data architectures and big data modeling techniques
- Experience with automated unit and integration testing practices
- Strong debugging skills and the ability to analyze technical code at scale
- Excellent communication and teamwork skills in a global environment
It is a strong plus if you have:
- Hands-on experience with Google Cloud tools like Cloud Dataflow, DataPrep, and Composer
- Background in data visualization tools such as Tableau
- Exposure to Enterprise Data Warehouse technologies
- Experience in customer-facing roles and stakeholder engagement
- Familiarity with agile methodologies such as Scrum or Kanban
,[Designing and deploying distributed data processing systems using Hadoop and Spark, Developing and optimizing data pipelines using Airflow and Scala, Integrating data platforms with GCP services such as BigQuery and Dataflow, Collaborating with DevOps teams to implement CI/CD pipelines using Jenkins, Building automated workflows to support data ingestion, transformation, and storage, Writing and maintaining high-performance SQL queries and scripts, Monitoring data pipeline performance and troubleshooting issues proactively, Supporting data migration projects from on-prem to cloud-based environments, Applying best practices for code versioning, testing, and deployment, Working closely with stakeholders to understand data requirements and propose scalable solutions] Requirements: Hadoop, Hive, Scala, SQL, Apache Spark, Apache Airflow, Google cloud, GCP, Jenkins, Git, GitHub, Tableau Additionally: Sport subscription, Private healthcare, International projects, Pluralsight.