Master Data Developer

Responsibilities:

• Design, build, and maintain robust ETL/ELT processes to ingest, transform, and deliver data across a modern Data Lake architecture.
• Develop and optimize distributed data processing workflows using Python and PySpark to handle large-scale datasets efficiently.
• Implement and refine partitioning strategies for data lake storage frameworks to balance query performance with storage costs.

Requirements:

• Solid experience with ETL processes and data pipeline development on AWS, with strong proficiency in Python and PySpark.
• Thorough understanding of SQL, including complex queries (CTEs, window functions, aggregations) and translating workloads from legacy RDBMS.
• Hands-on experience with AWS Glue, Athena, Redshift, and Data Lake architectures.

Benefits:

• Premium Healthcare, Meal Voucher, and Maternity and Parental leaves.
• Mobile services subsidy, Sick pay, and Life insurance.
• CI&T University, Colombian Holidays, and Paid Vacations.