Data Engineer

Data Engineer

eBay

Milan, Italy

What you will accomplish:

• You will design and develop robust, scalable, and efficient data pipelines to manage our Azure-based datalake.
• You will apply your expertise in writing reusable, testable, and efficient data scripts, working with data scientists and business analysts to architect and implement new data models and data integration to support business intelligence tools such as Tableau and Domo.
• You will use your analytical skills to perform deep dives into datasets to identify trends and insights, using Google Cloud tools to enhance data tracking and measure user engagement within our digital applications.
• You will ensure data quality, maintainability, and scalability through rigorous data validation, testing, and refactoring.
• You will conduct thorough requirements analysis and solution design, focusing on data modeling and database schema design within our Azure environment, and you will write the vital documentation supporting these activities.
• You will fix and resolve issues related to data pipelines and data quality to maintain high availability and reliability of data services.

What you will bring:

• Minimum 3 years of experience in a data engineering role, with hands-on experience in maintaining large scale databases, data warehouses or data lakes.
• Proficiency with BI tools such as Tableau and Domo, with a proven track record of developing actionable business insights from sophisticated datasets.
• Strong experience with Google Tag Manager, Google Analytics, and BigQuery, particularly in supervising and analyzing user engagement across digital platforms.
• Expertise in relational SQL and NoSQL databases, with specific experience in managing and optimizing data within Azure environments.
• Experience with data pipeline and workflow management tools such as Apache Airflow, AWS Data Pipeline, Google Cloud Dataflow with a preference for those experienced in an Azure context, like Azure Data Factory or Azure Synapse.
• Proficient in scripting languages used in data engineering such as Python, Java, C++, or Scala, with a preference for Python due to its extensive use in data analytics.
• Solid understanding of data warehousing solutions, particularly within Azure, and experience building ETL pipelines tailored to business needs.

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