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Big Data Engineer | Digital & Data

CIVITTA

Roles & Responsibilities

  • Hands-on experience with PySpark for large-scale data processing
  • Strong knowledge of Apache Kafka for real-time data streaming
  • Cloud platform experience across Azure, AWS, and/or GCP
  • Proven ability to design and optimize ETL/ELT pipelines

Requirements:

  • Design and implement data processing systems, including data warehouses, data lakes, and real-time processing platforms
  • Configure and manage technologies such as Hadoop, Spark, and Kafka, as well as cloud environments across Azure, AWS, and GCP
  • Build and maintain automated ETL/ELT processes for data collection, cleansing, and transformation
  • Ensure seamless, reliable data flow between diverse systems and sources, with a strong focus on data quality and consistency

Job description

Join Civitta - an international company with 750+ colleagues across 20+ countries. We focus on management consulting, funding, and digital solutions. Originating from Central and Eastern Europe, we also deliver projects across Central Asia, the Middle East, and the United States.

Help businesses turn strategy into digital solutions: from AI-powered marketing to data-driven products and custom software. We combine business thinking with technical execution.
Every day, you might build an e-commerce platform using predictive analytics, design a high-impact digital campaign, or develop a data-driven product that drives measurable results.

Take the step towards your journey with us and join us as a Big Data Engineer in the EU countries!


You will:
  • Design and implement data processing systems, including data warehouses, data lakes, and real-time processing platforms;
  • Configure and manage technologies such as Hadoop, Spark, and Kafka, as well as cloud environments across Azure, AWS, and GCP;
  • Build and maintain automated ETL/ELT processes for data collection, cleansing, and transformation;
  • Ensure seamless, reliable data flow between diverse systems and sources, with a strong focus on data quality and consistency;
  • Optimize data systems for high-volume, high-velocity workloads;
  • Design and implement distributed computing solutions that maintain performance at scale, proactively identifying and resolving bottlenecks.

    • Requirements:
  • Hands-on experience with PySpark for large-scale data processing;
  • Strong knowledge of Apache Kafka for real-time data streaming;
  •  Cloud platform experience across Azure, AWS, and/or GCP;
  • Proven ability to design and optimize ETL/ELT pipelines;
  • Familiarity with Hadoop ecosystems and distributed computing principles;
  • Solid understanding of data warehouse and data lake architectures;
  •  Nice to haves: experience with infrastructure-as-code tools (Terraform, Bicep), knowledge of data governance and security best practices, exposure to orchestration tools such as Apache Airflow or Azure Data Factory.

    • Benefits:
  • Flexible Working Hours – Manage your workday with flexibility and the option to work from home when needed, while enjoying our city-centre office as a convenient, collaborative workspace;
  • Culture & Connection – From team bonding activities like Christmas parties and summer events to spontaneous celebrations, monthly breakfasts, or team lunches, we celebrate wins—big or small—together;
  • Competitive salary.
    •
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