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AtScale/Denodo Data Virtualization Engineer
1 week ago
Experience :
- A minimum of 8 years of overall IT experience.
- 12 years of handson experience working with AtScale or Denodo data virtualization platforms.
- 5+ years of experience working with relational databases (e. g., Oracle, SQL Server, MySQL).
Technical Skills :
- Indepth knowledge of data warehousing and data modeling concepts (star schema, snowflake schema).
- Proven experience working with structured and unstructured data sources.
- Solid understanding of JDBC, XML, and web services APIs for data integration.
- Experience with production support activities, including deployments and troubleshooting.
- Proven ability to write efficient SQL queries to exploit databases.
- Working knowledge of data mapping techniques.
- Familiarity with programming languages like Java, Python, and R (a plus).
- Expertise in data source modeling for data warehouse environments.
Additional Skills :
- Experience with ETL (Extract, Transform, Load) processes, data storage, and BI tools.
- Handson experience with realtime data ingestion techniques (a plus).
- Familiarity with data visualization tools like Power BI or Tableau (a plus).
- Basic understanding of CI/CD (Continuous Integration/Continuous Delivery) using tools like Jenkins or Maven for automated deployments (a plus).
Soft Skills :
- Excellent communication and collaboration skills to work effectively with data analysts, developers, and other stakeholders.
- Strong problemsolving and analytical skills.
- A proactive and resultsoriented approach to work.
- Ability to learn new technologies quickly and adapt to changing requirements.
Responsibilities :
- Design and develop data virtualization layers using AtScale or Denodo to provide unified access to diverse data sources.
- Configure and manage data connections, transformations, and security within the data virtualization platform.
- Develop and maintain data virtualized views to meet specific business needs.
- Optimize data access performance and troubleshoot data quality issues.
- Collaborate with data analysts and developers to understand data requirements and design solutions.
- Stay uptodate with the latest advancements in data virtualization technologies and best practices.
- Participate in the implementation and ongoing support of data virtualization projects.
- Document data virtualization designs and configurations for future reference.
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