Senior Data Engineer (Fulfillment)

About the role

The Data Engineering department processes data within the retail and technology industry, including order and delivery data used to optimize logistics and delivery efficiency. The team manages critical customer-order, supplier, and product data to support fulfillment operations while maintaining data integrity and security.

As a Senior Data Engineer, you will lead the evolution of the data platform and data-pipeline architecture. You will design scalable, reliable, high-performing data solutions; influence architectural decisions; establish engineering best practices; and shape the technical direction of the data ecosystem.

You will optimize data flow, accessibility, and governance for cross-functional teams. You will work with software engineers, database architects, data analysts, data scientists, and product teams to deliver data-driven solutions, provide technical leadership, mentor engineers, and balance hands-on engineering with architectural ownership.

Hybrid working

This role requires you to be based in or near Kraków. You will spend 60% of your week (3 days) collaborating with colleagues at office locations or local sites and work remotely for the remainder.

Benefits

• Up to 20% yearly salary bonus based on individual and business performance
• Permanent contract from the start
• Tax-deductible expenses (IP)
• Private healthcare (LuxMed)
• Cafeteria and Multisport
• Additional 4 days of paid leave for well-being and family life
• Annual leave increase from 20 to 25 days for those not yet eligible for full holiday entitlement
• Certified technical training and learning platform (Udemy)
• Back-to-school day: 1 day off for parents of primary school children
• Fertility leave: up to 2 weeks of paid leave for IVF treatment
• Sports activities with a personal trainer in the office
• Referral bonus
• MacBook work tool

You will be responsible for

• Leading the design, development, and evolution of scalable, reliable, and secure data-pipeline architectures
• Building and optimizing large-scale data solutions that meet business, performance, and operational requirements
• Driving platform improvements through automation, infrastructure modernization, and continuous optimization
• Designing and maintaining robust data-ingestion, transformation, and delivery frameworks across diverse data sources
• Partnering with Product, Engineering, Analytics, and Business stakeholders to deliver scalable data solutions and influence technical direction
• Championing data quality, security, observability, and operational excellence across the data platform
• Building data products and self-service capabilities for analysts and data scientists
• Mentoring engineers, promoting best practices, and contributing to the long-term technical strategy of the data platform

Mandatory skills

• Data processing: Apache Spark with Scala or Python
• Data storage: Apache HDFS, CEPH S3, or a respective cloud alternative
• Resource manager: Apache Yarn or a respective cloud alternative
• Lakehouse: Apache Hive/Kyuubi or an alternative
• Workflow scheduler: Airflow or an alternative

Nice to have skills

• Functional programming
• Apache Kafka
• Kubernetes
• Stream processing
• CI/CD