Data Engineer

Responsibilities:

• Design and implement scalable ETL processes to extract, transform, and load data from diverse sources into our data warehouse.
• Collaborate with cross-functional teams to gather requirements and understand data integration needs.
• Perform data profiling, cleansing, and transformation to ensure data quality and consistency.
• Design optimized ETL workflows for performance and cost-effectiveness, leveraging AWS services.
• Document ETL processes, data mappings, and workflows for knowledge sharing and future reference.
• Stay updated on industry trends and best practices in ETL, data warehousing, and cloud technologies.
• Provide technical support and guidance to team members on ETL-related matters.
• Collaborate with stakeholders to understand product-specific data requirements, particularly with Workday data.

Qualifications:

• Proficiency in ETL tools and techniques, with hands-on experience in designing and implementing ETL processes.
• Strong understanding of data warehousing concepts and methodologies.
• Experience working with AWS Glue Jobs, S3, Redshift, and other AWS services.
• Familiarity with building and managing ETL pipelines in a cloud environment.
• Exposure to Workday data and understanding of its data model and integration capabilities.
• Experience in designing ETL solutions for integrating Workday data into enterprise systems is highly desirable.

Key Skills:

• Machine learning.
• NoSQL.
• ETL.
• Cloud computing.
• Data warehouse.
• Database management.
• SQL.
• Big data.
• Data visualization.