Description

You will design and implement data architecture solutions.

Responsibilities

• Build and optimize ETL pipelines using distributed processing frameworks.
• Design and implement data models for warehousing and analysis.
• Tune Amazon Redshift performance, schema, and workload management.
• Orchestrate data workflows using tools like Airflow, Step Functions, and Lambda.

Required Skills

• 3+ years of experience in data engineering.
• Expertise in distributed data processing using Spark, AWS Glue, or EMR.
• Proficiency in Python, PySpark, and SQL.
• Hands-on experience building and optimizing ETL pipelines.
• Solid background in Data Warehousing concepts (star/snowflake schema, dimensional modeling).
• Experience with the AWS ecosystem.
• Familiarity with Iceberg tables.

Key Skills

Education

Any Graduate