Capco
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Mid/Senior Data Engineer (Kraków/GCP)

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MidFull-time
#446123·Dodano wczoraj·0
Źródło: Capco
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Tech Stack / Keywords

PythonApache SparkHadoopLinuxGoogle Cloud PlatformETLSQLBigQueryApache AirflowDocker

Firma i stanowisko

Capco Poland is a global leader in technology and management consulting, specializing in digital transformation within the financial sector including banking, payments, capital markets, wealth, and asset management. The company emphasizes an agile, innovative work environment and focuses on building a talented professional team.

Wymagania

  • 2–4+ years of commercial experience in Data Engineering or a similar role.
  • Hands-on programming skills in Python.
  • Practical experience with Apache Spark, including building and maintaining data processing jobs.
  • Experience working with Hadoop or distributed data processing ecosystems.
  • Good knowledge of Linux and command-line environments.
  • Commercial experience with Google Cloud Platform (GCP) and relevant data services.
  • Understanding of ETL/ELT processes, data pipelines, and data transformation concepts.
  • Working knowledge of SQL and relational data concepts.
  • Understanding of data quality, monitoring, and troubleshooting practices.
  • Familiarity with Git and modern software development practices.
  • Ability to work effectively in an Agile environment and collaborate with distributed teams.
  • Good communication skills and English at a minimum B2 level.

Nice to have:

  • Experience with GCP services such as BigQuery, Cloud Storage, Dataproc, Dataflow, or Pub/Sub.
  • Experience in Financial/Banking domain.
  • Experience with orchestration tools such as Apache Airflow.
  • Familiarity with CI/CD processes for data solutions.
  • Knowledge of data modelling and data warehouse concepts.
  • Experience working with financial services or banking clients.
  • Familiarity with containerization technologies such as Docker or Kubernetes.

Obowiązki

  • Design, develop, and maintain scalable data pipelines and processing solutions.
  • Develop data transformation and processing workflows using Python and Apache Spark.
  • Work with large-scale datasets in distributed environments using Hadoop and related technologies.
  • Build and support cloud-based data solutions on Google Cloud Platform (GCP).
  • Develop reliable ingestion processes integrating data from multiple source systems.
  • Implement data transformations, validation rules, and data quality checks.
  • Troubleshoot data pipeline issues and support performance optimization.
  • Work with Linux-based environments including scripting, deployment, and operational activities.
  • Collaborate with Data Engineers, Architects, Analysts, and stakeholders to translate business requirements into technical solutions.
  • Participate in code reviews and follow software engineering and data engineering best practices.
  • Create and maintain technical documentation covering data flows, dependencies, configurations, and operations.
  • Support deployment, testing, stabilization, and ongoing maintenance of data solutions.
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