Must-Have
Strong experience in programming languages such as Python, PySpark, or Scala for data engineering tasks.
Design, develop, and maintain scalable and robust data pipelines on Databricks
Hands-on experience with cloud technologies, expertise in AWS/Azure data engineering services to handle large-scale data processing and real-time data streams.
In-depth knowledge of data warehousing solutions such as Amazon Redshift, Google BigQuery, and Snowflake for building and managing data warehouses.
Proficiency in designing, developing, and maintaining ETL (Extract, Transform, Load) processes using cloud services, ADF, Glue etc
Valuable-to-Have
Robust understanding of data modeling concepts and techniques to create effective and scalable data models.
Experience with version control systems such as Git for code management and collaboration.
Knowledge of data governance, data quality standards, and data security practices to ensure compliance and protection of sensitive information