Azure Data Engineer

Responsibilities

• Strong understanding of semantic models used in enterprise reporting and analytics.
• Expertise in dimensional modelling, including star and snowflake schema design.
• Practical experience implementing Slowly Changing Dimensions (SCD) Type 1 and Type 2.
• Ability to translate business requirements into scalable data models.
• Advanced Spark SQL.
• Proficiency in Spark SQL, including complex joins, aggregations, and transformations.
• Strong command over window functions, ranking functions, and analytical queries.
• Ability to troubleshoot performance issues and optimize Spark SQL queries.
• PySpark Development.
• Working knowledge of PySpark for data ingestion, transformation, and workflow orchestration.
• Ability to write and understand basic pyspark functions.
• Basic understanding of Spark architecture, including executors, partitions, and caching.