Contracting period: Long term project(1 year)

Location: Hybrid (Poland)

About the Role

We are looking for an experienced Senior (Big) Data Engineer to join large-scale data platform initiatives for an international technology-driven organization. The company builds and operates high-volume, low-latency data platforms, processing large amounts of event data through modern batch and streaming architectures.

This role is suited for a senior-level data engineer who enjoys working with distributed systems, event-driven data processing, and cloud-native technologies. The position requires fluency in Polish and location within Poland.

Your Profile

• 6–8 years of hands-on experience in Data Engineering roles

• Experience with at least one major cloud platform (GCP, AWS, or Azure); willingness to work in a GCP-based environment (prior GCP experience is a plus)

• Strong production experience with Apache Spark, using Python / PySpark

• Hands-on experience with streaming and event-driven architectures, using technologies such as:

  • Kafka

  • Google Pub/Sub

  • AWS Kinesis

  • Azure Event Hubs

• Strong SQL skills, including data transformations, analytical queries, and performance optimization

Nice-to-Have Skills

• Previous experience specifically in a Big Data Engineer role

• Background in JVM-based languages (Scala, Java, Kotlin)

• Familiarity with data lake or lakehouse architectures

• Experience implementing monitoring, observability, and data quality checks

• Exposure to high-throughput event processing systems

• Experience with CI/CD pipelines or Infrastructure-as-Code approaches

Your Responsibilities

• Design, build, and maintain scalable batch and streaming data pipelines

• Develop, optimize, and operate Apache Spark jobs using PySpark

• Work with event-driven and streaming platforms to process high-volume datasets

• Perform advanced data transformations and analytics using SQL

• Improve the performance, reliability, and observability of data pipelines

• Collaborate with analytics, platform, and product teams to deliver end-to-end data solutions

• Participate in technical and architectural decision-making

• Take end-to-end ownership of data solutions, from design through production

What You Can Expect

• Work on large-scale, data-intensive systems with real-world impact

• A technically challenging environment focused on distributed data processing

• Collaboration with cross-functional teams in a modern data platform ecosystem

• Opportunities to influence architecture, tooling, and best practices