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Data Engineer

In the role of Data Engineer, you will play a pivotal role in conceptualizing, developing, and maintaining robust data infrastructure and pipelines to facilitate efficient data processing, storage, and analysis. As a valued member of an international SCRUM team, you'll collaborate on diverse projects alongside experts in the field. Your focus may extend to spearheading the migration, modernization, and optimization of data infrastructure and workflows on Google Cloud Platform (GCP). Alternatively, you could take charge of OneDataLake pipeline development, integrate data into Data Vault, and strike a balance between IT and business demands to create streamlined pipelines in public cloud environments. Your involvement might also include training and fine-tuning generative language models or predicting 5G network usage and coverage. The array of opportunities is vast, allowing you the flexibility to choose a path. With your expertise flourishing, the potential for promotion to Lead Data Engineer awaits.

What will be your key responsibilities:

  • Designing and implementing scalable data architectures to ensure efficient storage, processing, and retrieval of large volumes of structured and unstructured data.
  • Collaborating with cross-functional teams, including data scientists, analysts, and software engineers, to comprehend data needs and develop tailored solutions.
  • Leading the development and maintenance of data pipelines, orchestrating the extraction, transformation, and loading (ETL) processes to ingest data from various sources into the data warehouse.
  • Optimizing data workflows, identifying performance bottlenecks, and implementing strategies to enhance data processing speed and efficiency.
  • Ensuring data quality and integrity through the implementation of data validation and cleansing techniques, as well as monitoring data pipelines for errors or inconsistencies.
  • Working closely with data governance teams to establish data security and compliance protocols, ensuring adherence to industry standards and regulations.
  • Continuously evaluating and integrating new technologies and tools into the data ecosystem, staying abreast of industry trends and best practices to enhance data engineering capabilities.
  • Mentoring and providing guidance to junior data engineers, fostering a collaborative and knowledge-sharing environment to encourage professional growth within the team.

What experience should you have:

  • A minimum of 3 years of experience in Data Engineering.
  • Excellent skills and knowledge of Python programming language and Java.
  • Expertise in SQL/no SQL databases, Data Warehouse, Big Data technologies, and BigQuery.
  • Experience with Spark, Hadoop, Kafka, and ETL/ELT processes.
  • Proficiency in cloud technologies (GCP, AWS, Azure), preferably Google Cloud.
  • Advanced soft skills, including communication and team cooperation.
  • Expert analytical skills and problem-solving abilities.

What do you get in return:

We believe in maintaining a balance between work and personal life. Our extensive work-life balance portfolio includes over 25 different benefits, focusing on financial well-being, learning and development, health and sports, and family and work-life balance. These benefits aim to enhance the personal and professional lives of our employees, providing them with the freedom to reconcile work, career growth, private life, and individual lifestyle.

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