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Senior Data Engineer

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Job Description - Senior Data Engineer

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

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