Data engineer
Posted 27 days ago · 0 applicants
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The role in plain words
- B.Sc. in Computer Science, Engineering, Mathematics, or Statistics
- 3+ years of hands-on experience as a Data Engineer
- 3+ years of experience with Python and Object-Oriented Programming (OOP)
- Proven practical experience with Spark for large-scale data processing
Extracted from the job description · kept up to date automatically
Who this suits
Full job description
Original listing · kept for referenceabra professional services is seeking a talented Data Engineer! We are looking for a Data Engineer to join our team and work on cutting-edge AI projects. In this role, you will be responsible for ingesting large volumes of new data, as well as deeply understanding and analyzing it in close collaboration with our Data Scientists. You will design and develop critical, diverse, and large-scale data pipelines across both Cloud and On-Premises environments.
Requirements: • Education: B.Sc. in Computer Science, Engineering, Mathematics, or Statistics – Must . • Experience: 3+ years of hands-on experience as a Data Engineer – Must . • Programming: 3+ years of experience with Python and Object-Oriented Programming (OOP) – Must . • Big Data: Proven practical experience with Spark for large-scale data processing – Must . • Deep understanding of designing, developing, and optimizing complex high-volume data systems. • Familiarity with data formats and optimization/partitioning techniques (Parquet, Avro, HDF5, Delta Lake). • Solid conceptual and practical understanding of Docker, Linux, CI/CD tools, and Kubernetes. • Experience with data pipeline orchestration tools such as Airflow or Kubeflow. • Understanding of core Machine Learning concepts and workflows.
Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- Hybrid
- B.Sc. in Computer Science, Engineering, Mathematics, or Statistics, 3+ years of hands-on experience as a Data Engineer, 3+ years of experience with Python and Object-Oriented Programming (OOP), Proven practical experience with Spark for large-scale data processing