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The BI Data Engineer is responsible for building and maintaining the data infrastructure that supports Business Intelligence and data analytics activities, for designing, constructing, and maintaining the systems and architectures that allow large volumes of data to be processed and stored, architectures such as databases and large-scale processing systems.

Key Responsibilities:

• Designs and implements efficient and robust architectures for handling big data. This includes choosing appropriate storage solutions, data warehouses, and data lakes.
• Develops data pipelines to extract, transform, and load data from various sources into the data storage systems. These pipelines ensure data consistency, quality, and availability.
• Manages databases and data warehouses, ensuring their performance, scalability, and security. Optimizes queries, indexes, and data models for efficient data retrieval and storage.
• Works closely with data scientists and analysts to provide them with the data they need for analysis and reporting. This involves understanding the data requirements of different stakeholders and creating data sets that meet those needs.
• Implements processes and tools to ensure data quality, integrity, and consistency. This includes data validation, cleansing, and monitoring to identify and address data quality issues.
• Collaborates with cross-functional teams, including data scientists, analysts, and software engineers, to understand their data needs and requirements. Effective communication skills are essential for translating these requirements into technical solutions.
• Stays updated on the latest technologies and best practices in data engineering to continuously improve systems and processes. This involves experimenting with new tools and techniques to enhance efficiency, scalability, and reliability.

Requirements:

• Education: Bachelor/Master’s Degree in Computer Science, Business Analytics, Information Technology, Data Science or a related field is often required.
• Languages: Italian; Fluent English; written and verbal communication.
• Experience: At least 2 years in a similar role + at least 1 year of prior experience in data-related roles such as data analyst, data scientist, or junior data engineer can be beneficial.

Other Information and Specific Skills:

• Knowledge of at least one of the following Programming Languages: SQL, Python, Java/Scala.
• Knowledge of Database Technologies:
  • Relational Databases: SQL Server, Oracle, PostgreSQL.
  • NoSQL Databases knowledge is a plus: MongoDB, Cassandra, Redis.
• Familiarity with data warehousing concepts and technologies like SAP HANA, Snowflake, Amazon Redshift, or Google BigQuery.
• Experience with ETL (Extract, Transform, Load) tools such as Azure Data Factory, Talend, or Microsoft SSIS.
• Knowledge of BI tools such as Power BI, QlikView, Looker, or SAP BusinessObjects.
• Experience with cloud services from providers like Azure or Google Cloud Platform (GCP), especially their data-related services (e.g. Azure Synapse Analytics).
• Understanding of data modeling concepts and techniques.
• Analytical Thinking/Problem Solving: ability to analyze and interpret complex data sets.
• Collaboration: ability to work collaboratively with other teams, such as data scientists, analysts, and business stakeholders.
• Stay Current: keep up-to-date with the latest trends and technologies in the BI and data engineering field through blogs, forums, webinars, and conferences.