Data Engineer (Stores/Customer Order)

About the role

The Data Engineering department processes retail order and delivery data to optimize logistics and delivery efficiency, manages critical customer order, supplier, and product data for fulfillment operations, and maintains data integrity and security.

As a Data Engineer, you will expand and refine data and data-pipeline architecture, optimize data flow and collection for cross-functional teams, and work closely with software developers, database architects, data analysts, and data scientists. The role requires self-direction and the ability to support the data requirements of multiple teams, systems, and products.

What is in it for you

Hybrid working

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

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 access to a 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

• Creating and maintaining optimal data-pipeline architecture
• Assembling large, complex data sets that meet functional and non-functional business requirements
• Identifying, designing, and implementing internal process improvements, including automating manual processes, optimizing data delivery, and redesigning infrastructure for scalability
• Building infrastructure for extracting, transforming, and loading data from a wide range of data sources
• Building analytics tools that use data pipelines to provide actionable insights into customer acquisition, operational efficiency, and key business performance metrics
• Working with stakeholders, including Executive, Product, Data, and Design teams, to resolve data-related technical issues and support data-infrastructure needs
• Keeping data separated and secure
• Creating tools for analytics and data-science teams to help build and optimize products
• Working with data and analytics experts to improve data-system functionality

You will need

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