Data Engineer

Quick Facts

• Location/Work model: Wrocław (hybrid) — 3 days per week in the client office

• Start: According to the candidate’s notice period

• Engagement: B2B

• Rate: 140–160 PLN/h + VAT

Description

Design and expand high-performance, highly available, low-latency distributed transaction systems. Build and optimize data pipelines using Spark, Databricks, and PySpark, and integrate Kafka-based streaming architectures. Deploy and maintain Azure Cloud solutions with Kubernetes, with CI/CD automation and Level 3 (DEV) production support in an Agile team.

Responsibilities

• Design and develop high-performance, highly available, low-latency distributed transactional systems

• Create and optimize data pipelines with Spark, Databricks, and PySpark

• Integrate and operate Kafka-based streaming architecture

• Implement and maintain Azure Cloud solutions using Kubernetes

• Build and automate CI/CD pipelines and DevOps practices

• Communicate technical and functional details to business stakeholders and IT teams

• Provide Level 3 support (DEV) in a demanding production environment

• Work in a software team using Agile methodology

Benefits

• Clear collaboration terms in a stable market position

• Additional benefits: medical package, sports package, free accounting support (up to 3 entries per month)

Requirements

• Minimum 7 years of experience as a Data Engineer or related role

• Very strong knowledge of Spark, Databricks, and PySpark

• Knowledge of Java and Python

• Deeper experience with Azure Cloud

• Experience with Kubernetes

• Experience with Kafka architecture and streaming pipelines

• Knowledge of DevOps tooling and CI/CD pipeline creation

• English at least B2

Might be a plus

• Experience providing L3 (DEV) technical support in a dynamic production environment