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Cloud Data Engineer for Scalable Solutions
hace 1 semana
Overview
This role is part of Intel's efforts to develop cutting-edge cloud-based solutions. The ideal candidate will have a strong background in Azure services, data governance, and metadata management.
Key Responsibilities
- Create scalable and resilient solutions using Azure Functions, Logic Apps, and other Azure services
- Implement event-driven patterns for data integration and processing
- Manage and maintain data assets in Collibra Data Catalog
- Define and enforce data governance standards and policies within Collibra
- Collaborate with data stewards and data owners to ensure data quality and compliance
- Support data lineage and metadata management efforts within Collibra
- Implement and maintain data quality processes using Informatica Cloud Data Quality
- Develop and manage data quality rules, validations, and cleansing routines
- Collaborate with data stakeholders to improve data quality across the organization
- Monitor and report on data quality issues and improvements
Required Skills and Qualifications
- Bachelor's degree in Computer Science, Information Technology, or a related field
- 4 years of experience in programming languages like C#, Python, or JavaScript
- Experience with data visualization tools like Tableau, Power BI, or similar
- Strong knowledge of Azure services, including Azure Functions, Logic Apps, and Event Grid
- Data analysis tools such as SQL, Python, or R
- Certifications in Collibra and Informatica
- Azure certifications
- Experience in data governance and metadata management using Collibra Data Catalog
- Proficiency in Informatica Cloud Data Quality tools and processes
- Strong knowledge of data quality best practices
- Familiarity with event-driven architectures, messaging patterns, and stream processing
Benefits
We offer a comprehensive compensation package that includes competitive pay, stock, bonuses, and benefits such as health, retirement, and vacation plans.
Working Model
This role will be eligible for our hybrid work model, allowing employees to split their time between working on-site at their assigned Intel site and off-site.