Senior Data Engineer (AFC area) (Luminor Bank AS Lietuvos skyrius)

Job description:
Join us as a Senior Data Engineer in Anti-Financial Crime & Compliance Technology team!
Yes, you can! That's our attitude towards our work, ambitions, ideas, and relationships. We at Luminor believe that anyone has the potential to achieve big things and encourage everyone to achieve them, professionally and personally.
Whoever you are and whatever your role is, with Luminor, you will get a once-in-a-lifetime opportunity to build a local banking champion.
As part of our Pan-Baltic Anti-Financial Crime & Compliance Technology team, you’ll be building scalable, secure, and high-performing data solutions that power our financial crime prevention controls and tools. You’ll work closely with cross-functional teams to ensure seamless data flows across systems, and help us move towards a modern, decentralized data architecture inspired by data mesh principles.
Design, implement, and continuously improve systems for data ingestion, processing, storage, and sharing
Build and optimize data architectures for performance, scalability, and reliability
Develop and maintain ETL/ELT pipelines using modern tools and frameworks
Design and operate Apache Spark data pipelines on Amazon EMR and AWS Glue, using Apache Iceberg tables across Bronze, Silver, and Gold layers of the Medallion framework
Ensure seamless integration and synchronization across lending automation systems, retail lending tools and processing systems
Uphold high standards of data quality, security, availability, and performance within data mesh principles
Collaborate with analysts, software engineers, and business stakeholders to understand data needs and deliver solutions
Perform technical specification and code reviews, integration testing, troubleshoot software, and fix defects
Implement monitoring and alerting for data workflows
Gain expertise in a variety of banking processes and products
Work as part of a cross-functional Agile development team in a Pan-Baltic, international environment according to data mesh principles
Requirements:
Proven experience with SQL /Python and data warehousing
Hands-on experience with cloud platforms (AWS, Azure, or GCP)
Hands-on experience with Apache Spark, including performance tuning and development of scalable pipelines
Experience implementing lakehouse architectures with Apache Iceberg and Medallion layers, preferably using Amazon EMR, AWS Glue, Amazon S3, and the AWS Glue Data Catalog
Familiarity with data pipeline tools like Apache Airflow or dbt
Experience with data warehousing solutions (Snowflake, BigQuery, Redshift, SAP Sybase IQ)
Experience with ETL/ELT designer tools
Knowledge of solution integrations (real-time, message-based, event-driven)
Experience within the Anti-Financial Crime/AML domain is a strong advantage
Ability to take ownership and drive initiatives independently
Fluent English is required in spoken and written communication due to working on the Pan-Baltic level
Company offers:
Flexibility. Flexible working hours,…