Senior Data Engineer (Big Data)

DataEdge SRL; Warszawa; On-site; PLN 120,000 - 160,000; Full time

Job summary

DataEdge SRL is seeking an experienced Senior (Big) Data Engineer to contribute to large-scale data platform initiatives. This role involves designing, building, and maintaining scalable data pipelines utilizing cloud technologies, particularly in a GCP-based environment. The ideal candidate should possess strong SQL skills and a background in event-driven architectures.

Candidates need to have 6–8 years of data engineering experience and fluency in Polish. This position offers a hybrid work model with opportunities for growth in a technologically advanced setting.

Qualifications

• 6–8 years of experience in Data Engineering roles.
• Experience with a major cloud platform (GCP, AWS, or Azure).
• Production experience with Apache Spark, using Python/PySpark.

Responsibilities

• Design, build, and maintain scalable batch and streaming data pipelines.
• Develop, optimize, and operate Apache Spark jobs using PySpark.
• Collaborate with analytics, platform, and product teams.

Skills

Cloud platform experience (GCP, AWS, or Azure)

Apache Spark and PySpark

SQL skills

Event-driven data processing

Tools

Kafka

Google Pub/Sub

AWS Kinesis

Job description

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

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