Bachelor's or Master's degree in Computer Science or a related field, with at least 6 years of experience in Information Technology, or equivalent combination of education and work experience.
Proficiency in one or more programming languages (e.g., Python, Java, Scala)
6+ years of experience in data engineering, with a focus on designing and implementing large-scale data systems
5 + years of hands-on experience in writing complex, highly optimized queries across large data sets using AWS Redshift, Oracle and SQL Server.
5 + years of hands-on experience using AWS Glue, python/spark to build ETL pipelines in a production setting, including writing test cases
Strong understanding of database design principles, data modeling, and data governance
Proficiency in SQL, including query optimization, indexing, and performance tuning
Experience with data warehousing concepts, including star and snowflake schemas
Experience with data storage solutions such as relational databases (Oracle, SQL Server), NoSQL databases and cloud-based data warehouses (Redshift)
Experience with data processing frameworks such as Apache Kafka, Fivetran
Experience in building ETL pipelines using AWS Glue, Apache Airflow, and programming languages including Python and PySpark
Understanding of data quality and governance principles and best practices
Experience with AWS services and best practices