Senior Data Engineer (Java/Scala, Spark, AWS)

EPAM Systems; Poland; On-site; PLN 240,000 - 400,000; Full time

Job summary

EPAM Systems in Poland is seeking a Senior Data Engineer to design, build, and maintain large-scale data pipelines and distributed processing systems powering AI-driven initiatives. You will leverage Spark, AWS, and modern data architectures to deliver secure, scalable data solutions.

The role emphasizes data modeling for lakehouse architectures, data quality and governance, and collaboration with cross-functional teams to support Gen AI and ML applications.

Qualifications

• 5+ years of experience in Data Engineering with exposure to Gen AI/ML-based applications.
• Background in building and maintaining large-scale data pipelines and distributed processing systems using Spark with Java or Scala.
• Familiarity with AI/ML, Generative AI, or data platforms supporting AI-driven initiatives.
• Expertise in AWS cloud environments and cloud-native architectures.
• Advanced proficiency in SQL.
• Skills in data modeling and modern data lakehouse architectures.
• Understanding of data quality, governance, monitoring, and operational best practices.
• Competency in building secure, scalable, and highly available data solutions.
• Showcase of ETL/ELT development experience.
• Proficiency in English at an Upper-Intermediate level (B2) or higher.
• Nice to have: Hands-on experience with Databricks or Snowflake.
• Background in Financial Services

Responsibilities

• Design, build, and maintain large-scale data pipelines and distributed processing systems using Spark
• Develop and support data platforms that enable AI/ML and Generative AI applications
• Architect and implement solutions within AWS cloud environments using cloud-native patterns
• Build and optimize ETL/ELT workflows to support analytical and operational use cases
• Implement data modeling strategies aligned with modern data lakehouse architectures
• Ensure data quality, governance, and monitoring across all data assets
• Deliver secure, scalable, and highly available data solutions following operational best practices
• Collaborate with cross-functional teams to support AI-driven business initiatives
• Write advanced SQL queries and production-grade code in Java or Scala

Skills

Spark

AWS

Java

Scala

SQL

Data modeling

Data lakehouse

Data quality

ETL/ELT

Gen AI familiarity

Financial Services

Tools

Databricks

Snowflake

Job description

We are seeking a Senior Data Engineer to design, build, and maintain large-scale data pipelines and distributed processing systems that power AI-driven initiatives. In this role, you will leverage your expertise in AWS, Spark, and modern data architectures to deliver secure, scalable, and highly available data solutions supporting Gen AI and ML applications.

Responsibilities

• Design, build, and maintain large-scale data pipelines and distributed processing systems using Spark
• Develop and support data platforms that enable AI/ML and Generative AI applications
• Architect and implement solutions within AWS cloud environments using cloud-native patterns
• Build and optimize ETL/ELT workflows to support analytical and operational use cases
• Implement data modeling strategies aligned with modern data lakehouse architectures
• Ensure data quality, governance, and monitoring across all data assets
• Deliver secure, scalable, and highly available data solutions following operational best practices
• Collaborate with cross-functional teams to support AI-driven business initiatives
• Write advanced SQL queries and production-grade code in Java or Scala

Requirements

• 5+ years of experience in Data Engineering with exposure to Gen AI/ML-based applications
• Background in building and maintaining large-scale data pipelines and distributed processing systems using Spark with Java or Scala
• Familiarity with AI/ML, Generative AI, or data platforms supporting AI-driven initiatives
• Expertise in AWS cloud environments and cloud-native architectures
• Advanced proficiency in SQL
• Skills in data modeling and modern data lakehouse architectures
• Understanding of data quality, governance, monitoring, and operational best practices
• Competency in building secure, scalable, and highly available data solutions
• Showcase of ETL/ELT development experience
• Proficiency in English at an Upper-Intermediate level (B2) or higher
• Nice to have: Hands-on experience with Databricks or Snowflake, with the ability to work across modern cloud-based data platforms (experience with both is advantageous)
• Background in Financial Services