Azure Data Engineer:
In the role of Azure Data Engineer, you will design, develop, and maintain data processing systems using Azure Data Lake Storage, Azure Synapse Analytics, Snowflake, Python, and SQL. You'll collaborate with Product Owners, Data engineers, Analysts, and other stakeholders to understand requirements and deliver solutions in an entrepreneurial culture where teamwork is encouraged, excellence is rewarded, and diversity is valued.
Locations for this position are Mexico (Monterrey, GDL, CDMX) on hybrid mode as per Infosys Mexico policy .
Basic Qualifications:
- Bachelor's degree or foreign equivalent from an accredited institution.
- At least 3-5 years of experience in Information Technology.
- Excellent English communication skills.
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- 3-5 years of experience with Python and SQL.
- 3-5 years designing and developing large-scale data processing pipelines using Azure Databricks and related technologies.
- Expertise in Azure Data Lake Storage, Azure Synapse Analytics, and Snowflake.
- Experience with Azure Data Factory, Azure Functions, and Azure Logic Apps.
- Familiarity with Azure Data Factory for orchestration and Event Hubs/Service Bus for data streaming.
- Strong knowledge of modern data warehouse architecture and data modeling.
- Experience with Snowflake features such as Time Travel, Zero-Copy Cloning, and Snow pipe.
- Experience with Hadoop, HDFS, Hive and other Big Data technologies.
- Understanding of dimensional modeling, data vault, and other data warehousing methodologies.
- UNIX shell scripting will be an added advantage in scheduling/running application jobs.
- 3-5 years in project development lifecycle activities and maintenance/support.
- Experience working in Agile environments.
- Ability to translate requirements into technical solutions meeting quality standards.
- Collaboration skills in diverse environments to identify and resolve data issues.
- Strong problem-solving and analytical abilities.
- Experience in global delivery environments.
- Commitment to staying current with industry trends in modern data warehousing.