Senior Data Engineer – Payments Unit

Role Overview

• Design, build, and optimize data ingestion, transformation, and processing pipelines using Apache Spark–based platforms (e.g., AWS EMR, Glue Jobs, Databricks, Snowflake/Snowpark), along with AWS services (Amazon S3, Athena), and Kafka.
• Implement and maintain scalable solutions aligned with Data Lakehouse architecture and modern data engineering best practices.
• Use SQL and Python to develop robust data workflows, automation scripts, and transformation logic.
• Understand data models (conceptual, logical, and physical) and implement them as solutions.
• Develop and manage YAML-based configurations for pipeline metadata, orchestration, and schema definitions.
• Ensure end-to-end data quality, validation, lineage, security, availability, and performance across data assets.
• Collaborate closely with system analysts, data analysts, product teams, and software engineers to understand requirements and deliver dependable data solutions.
• Apply data product thinking when designing datasets and interfaces to support self-service analytics and reusable data assets.
• Support orchestration workflows on AWS MWAA (Managed Apache Airflow) or similar pipeline management platforms.
• Monitor, troubleshoot, and optimize data pipelines in production environments.

Requirements

• 3–5 years of experience as a Data Engineer or similar role
• Strong experience with AWS data stack : S3, EMR, Glue data catalog, Kafka, Athena, IAM and orchestration tools like MWAA
• Strong programming experience with Python , including writing clean, maintainable scripts
• Expertise in SQL and performance optimization
• Strong understanding of Data Lakehouse, ETL/ELT architectures , and distributed data processing
• Practical experience in data modeling and industry‑standard modeling techniques
• Proficiency with YAML for configuration and pipeline metadata management
• Strong communication and documentation skills
• Detail‑oriented with a strong commitment to high-quality, reliable data delivery
• Payments industry experience and BIAN exposure are a plus
• Fluent English is required in spoken and written communication due to working on the Pan-Baltic level

Tech Stack

• Airflow
• Apache
• AWS
• ETL
• Kafka
• Python
• Spark
• SQL

Benefits

• Flexibility. Flexible working hours, Hybrid work, and the possibility to work from anywhere in the EU, Iceland, Switzerland, and the UK (in total 90 days per year)
• International teams. Teams that go outside Pan-Baltic borders, where people value challenging work together with good humor and having fun
• Culture. You’ll be joining a team where things move fast, ideas flow freely, and change is part of the everyday. It’s a dynamic environment that keeps you learning, growing, and never bored
• More vacation. Additional weeks of vacation are available to all employees who have been in the company for 1 year or more
• Volunteer time off. We care about giving back to society, therefore, you will get additional days off for volunteering purposes
• Paid leave. We are proud of our employees who are participating in military training. Therefore, Luminor offers 30 fully paid calendar days for military training every year
• Health benefits. A competitive benefits package in addition to your salary that includes health insurance after the first 3 months pass in all three Baltic states, as well as Health days in case of your absence due to sickness without a doctor's note needed
• Wellbeing. Access to tools and resources that help you feel good and be productive at work and in life
• Professional growth. Internal and external training programs, LinkedIn learning, workshops, conferences, online training, etc
• Special Offer for Luminor products & services. Enjoy special offers & pricing for products and services provided by Luminor