Description

Key Responsibilities
Design and develop scalable cloud-native data pipelines.
Build and optimize batch and distributed data processing solutions.
Manage data lake and warehouse environments.
Ensure data quality, performance, security, and reliability.
Partner with business and analytics teams to deliver reporting and data solutions.
Support data migration, modernization, and platform enhancement initiatives

Must-Have Skills:
ETL, AWS Redshift, SQL, Python 
10+ years of Data Engineering/Data Warehouse experience.
Strong hands-on experience with AWS (EMR, S3, Glue Catalog, MWAA/Airflow).
Expertise in PySpark, Python, and SQL.
Experience building and maintaining ETL/ELT pipelines.
Strong data warehousing experience with Teradata, Oracle, Redshift, and relational databases.
Experience with Apache Iceberg, data lakes, and large-scale data processing.
Hands-on experience with Airflow orchestration and workflow automation.
Strong performance tuning, data modeling, and database optimization skills.
Experience working in Agile environments and collaborating with distributed teams

Key Skills

Education

Bachelor's degree