Data Engineer (Hadoop)

Industry: banking

Location: fully remote (candidates must be based in Poland)

Languages: fluent Polish and English

Contract: B2B

The Hadoop Data Engineer plays a critical role in enhancing the data processing capabilities within the organization, leveraging cloud technologies for efficient data handling and migration. The primary objective is to build and maintain robust data processing architectures that facilitate the flow of information and insights in a scalable manner.

Main Responsibilities:

• Develop and maintain data processing systems using Hadoop, Apache Spark, and Scala.
• Design and implement data migration processes on the Google Cloud platform.
• Create solutions for data handling and transformation utilizing SQL and other relevant tools.
• Collaborate with stakeholders to ensure data architecture aligns with business needs.
• Engage in automated testing and integration to ensure smooth deployment processes.
• Debug code issues and communicate findings with the development team.
• Apply big data modeling techniques for effective data representation.
• Adapt to dynamic environments and embrace a proactive learning attitude.

Key Requirements:

• 5+ years of experience in Hadoop, Hive, HDFS, and Apache Spark.
• Proficiency in Scala programming.
• Hands-on experience with Google Cloud Platform, especially Big Query and Cloud Dataflow.
• Strong understanding of SQL and relational database technologies.
• Experience with version control tools (Git, GitHub) and CI/CD processes.
• Ability to design large scale distributed data processing systems.
• Strong interpersonal skills and teamwork abilities.
• Experience in Enterprise Data Warehouse technologies.
• Exposure to Agile project methodologies (Scrum, Kanban).
• Google Cloud Certification - nice to have.
• Experience with customer-facing roles in enterprise settings.
• Exposure to Cloud design patterns.