Data Engineer for Business Intelligence
4 settimane fa
Job Title: Data Engineer for Business Intelligence
Job Summary:
Datalogic is seeking a highly skilled Data Engineer to join our ICT Business Demand & Applications team. The successful candidate will play a crucial role in enabling DL Functions to leverage their data assets effectively for decision-making, product development, and business growth.
Key Responsibilities:
- Design and implement efficient architectures for handling big data, including choosing appropriate storage solutions, data warehouses, and data lakes.
- Develop data pipelines to extract, transform, and load data from various sources into the data storage systems, ensuring data consistency, quality, and availability.
- Manage databases and data warehouses, ensuring their performance, scalability, and security, and optimizing queries, indexes, and data models for efficient data retrieval and storage.
- Collaborate with data scientists and analysts to provide the data needed for analysis and reporting, understanding the data requirements of different stakeholders and creating data sets that meet those needs.
- Implement processes and tools to ensure data quality, integrity, and consistency, including data validation, cleansing, and monitoring to identify and address data quality issues.
- Stay updated on the latest technologies and best practices in data engineering to continuously improve systems and processes.
Requirements:
- Bachelor's or Master's degree in Computer Science, Business Analytics, Information Technology, Data Science, or a related field.
- Fluent English, written and verbal.
- At least 3 years of experience in data-related roles, such as data analyst, data scientist, or junior data engineer.
Preferred Skills:
- Knowledge of at least one programming language, such as SQL, Python, or Java/Scala.
- Knowledge of database technologies, such as SQL Server, Oracle, or PostgreSQL, and NoSQL databases, such as MongoDB, Cassandra, or Redis.
- Familiarity with data warehousing concepts and technologies, such as SAP HANA, Snowflake, or Amazon Redshift or Google BigQuery.
- Experience with ETL 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.
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