Senior Data Scientist

Senior Data Scientist - AI-Driven Data Engineering 

Location: Krakow  

Contract Type: 6 Month  
Job Type: Hybrid 

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  Work with cutting-edge AI-assisted coding tools in your daily development 

  
  

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  Build and operate scalable batch and streaming data pipelines using Apache Spark and Apache Beam 

  
  

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  Collaborate with Analytics and Platform Engineers on cloud-based data solutions 

  
  

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  Gain exposure to data quality, governance tooling and real-time streaming systems 

  
  

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  Join a company investing in advanced GCP data services and modern data infrastructure 

  
  

Company Overview 

Our client is a technology-focused organisation operating in Krakow, committed to building robust data infrastructure that supports business intelligence and analytics capabilities. They work with modern cloud-based data platforms and are investing in AI-driven workflows to enhance their data processing capabilities. The company values collaboration across engineering teams and maintains a focus on data quality, governance and scalable solutions that support real-time and batch processing needs. 

They are currently seeking a Senior Data Scientist to join their team in Krakow on a contract basis. This role offers the opportunity to work with modern data engineering frameworks and AI-assisted development tools while contributing to the design and operation of scalable data pipelines. 

Position Overview 

As a Senior Data Scientist, you'll play a central role in designing, building and operating data pipelines that process information at scale. You'll work with distributed data processing frameworks, orchestrate complex workflows, and develop transformations that ensure data quality across the organisation. Your work will directly support analytics and business intelligence initiatives, enabling data-driven decision-making across the business. This position offers hands-on experience with modern cloud platforms, streaming systems and AI-enhanced development practices. 

Responsibilities 

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  Design and build scalable batch and streaming data pipelines 

  
  

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  Implement distributed data processing using Apache Spark and Apache Beam 

  
  

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  Orchestrate workflows with Apache Airflow to ensure efficient data management 

  
  

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  Develop and maintain data transformations using SQL and dbt 

  
  

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  Collaborate with Analytics Engineers and Platform Engineers on project execution 

  
  

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  Enhance data processing capabilities through AI-driven workflows 

  
  

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  Support business intelligence needs through analytics-driven use cases 

  
  

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  Improve data integrity using quality and governance tooling 

  
  

Requirements 

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  4-6 years of experience in data engineering or related field 

  
  

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  Strong experience with Apache Airflow and distributed data processing frameworks like Apache Spark 

  
  

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  Proficiency in Python and SQL for data pipeline development 

  
  

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  Mandatory familiarity with AI-assisted coding tools for day-to-day development 

  
  

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  Experience with GCP data services for managing cloud-based data solutions 

  
  

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  Knowledge of data transformation tools such as dbt 

  
  

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  Experience with streaming systems for real-time data processing 

  
  

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  Exposure to data quality or governance tooling 

  
  

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  Familiarity with analytics or business intelligence use cases 

  
  

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  Understanding of Apache Beam for batch and streaming data processing 

  
  

Benefits 

While specific benefits details are being finalised, this contract position offers the opportunity to work with modern data engineering technologies and AI-assisted development tools. You'll collaborate with experienced Analytics and Platform Engineers, gaining exposure to cloud-based data solutions, streaming systems and data governance practices. This role provides hands-on experience with industry-standard frameworks and the chance to contribute to scalable data infrastructure that supports critical business intelligence needs. 

How to Apply 

To apply for this role please submit your CV using the form below or email [email protected]