Data Engineer

About the role

The Data Engineering department processes data within the retail and technology industry. Its responsibilities include:

• Analyzing order and delivery data to optimize logistics processes and delivery efficiency
• Managing data related to customer orders, suppliers, and products to support fulfillment operations
• Maintaining data integrity and security while processing order and delivery information

As a Data Engineer, you will expand and refine data and data-pipeline architecture, while optimizing data flow and collection for cross-functional teams. You will work closely with software developers, database architects, data analysts, and data scientists on data-driven initiatives, ensuring a consistent data-delivery architecture across projects.

This role requires a high level of 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 each week collaborating with colleagues at office locations or local sites and the remainder working remotely.

Our 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 to support well-being and family life
• Annual leave increase from 20 to 25 days for those not yet eligible for the full holiday entitlement
• Certified technical training and 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 as a work tool

You will be responsible for

• Creating and maintaining optimal data-pipeline architecture
• Assembling large, complex datasets that meet functional and non-functional business requirements
• Identifying, designing, and implementing internal process improvements, including automation of manual processes, data-delivery optimization, and infrastructure redesign for scalability
• Building infrastructure for optimal extraction, transformation, and loading of data from a wide variety of sources
• Building analytics tools that use data pipelines to provide actionable insights into customer acquisition, operational efficiency, and other 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 data tools that help analytics and data-science team members build and optimize products
• Working with data and analytics experts to improve the functionality of data systems

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