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

Technologies we use

About the project

This is how we organize our work

This is how we work

Your 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

Our 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

Optional

• 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

What we offer

Development opportunities we offer