Hybrid Data Engineer - Spark, Scala & Java Pipelines

Sii Polska; Warszawa; Hybrid; PLN 180,000 - 240,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Sii Polska in Warsaw is seeking a Data Engineer to help modernize our backend data processing platform on a Big Data stack within an internal cloud. The role offers a hybrid work model with 2-3 days in the office each week.

You will design and maintain scalable data pipelines using Scala and Apache Spark, implement ETL/ELT processes, and develop Java-based data processing components. Collaboration with cross-functional teams is essential.

Qualifications

• Minimum 4 years of experience as a Data Engineer on large-scale data projects.
• Strong knowledge of Scala and Apache Spark.
• Hands-on Java development for backend data processing.
• Experience designing ETL/ELT data pipelines.
• Good SQL skills and relational databases expertise.
• Experience with distributed systems and Big Data environments.
• Proficiency in Polish and English; residency in Poland.

Responsibilities

• Design, develop, and maintain scalable data pipelines with Scala and Spark.
• Implement ETL/ELT processes and transformations for large data volumes.
• Develop and maintain data processing components using Java.
• Optimize performance of Spark applications and workflows.
• Integrate data from diverse sources for banking systems usage.
• Collaborate with Data Engineers, Developers, Analysts and business teams.

Skills

Scala

Apache Spark

Java

ETL/ELT

SQL

Distributed systems

Big Data

Polish language

English language

Job description

Sii Polska in Warsaw is seeking a Data Engineer to help modernize our backend data processing platform on a Big Data stack within an internal cloud. The role offers a hybrid work model with 2-3 days in the office each week.

You will design and maintain scalable data pipelines using Scala and Apache Spark, implement ETL/ELT processes, and develop Java-based data processing components. Collaboration with cross-functional teams is essential.