Description

You will build and maintain data pipelines using Python and modern data warehousing practices.

Responsibilities

• Develop and implement ETL/ELT data pipelines for structured and semi-structured data.
• Write complex SQL queries and stored procedures for data transformation and ingestion.
• Manage data processing workflows, ensuring proper scripting and error handling.
• Tune database performance and troubleshoot data pipeline issues.

Required Skills

• 9+ years of hands-on development experience in Python as an ETL/ELT Data Engineer.
• Expertise in PySpark and Python Data Frame for data processing.
• Strong proficiency in complex SQL, stored procedures, and performance tuning.
• Experience with data ingestion, data warehousing, and ETL processes.
• Familiarity with AWS environment.
• Knowledge of Snowflake, including SNOW SQL and Snowpark.
• Experience with Data Quality implementation in data pipelines.
• Ability to articulate technical concepts clearly.

Preferred Skills

• Working knowledge of job scheduling tools like Control M, Autosys, or Airflow.
• Experience with Snowflake Cloud Data Warehouse on AWS Data Lake.
• SnowPro Core Certification.

Key Skills

Education

Any Gradute