Description

You will design and manage data architecture and ETL pipelines within an AWS environment, solving analytical problems independently.

This role is on-site.

Responsibilities

• Build and maintain ETL pipelines to process large datasets.
• Develop data warehousing solutions using dimension modeling.
• Write and optimize complex SQL queries for performance tuning.
• Manage AWS infrastructure using Lambda, Event Bridge, Step Functions, SNS, and SQS.

Required Skills

• 9+ years of experience in data engineering and data warehousing.
• Proficiency in Python development and API integration.
• Hands-on experience with Spark or PySpark.
• Expertise with AWS Glue, EMR, Kinesis, or Kafka.
• Experience with AWS Redshift, MS SQL Server, or Postgres.
• Direct experience using AWS Lambda, Event Bridge, Step Functions, SNS, and SQS.
• Understanding of IAM Roles and Policies.
• Strong dimension modeling and SQL performance tuning skills.

Preferred Skills

• Experience with Airflow for workflow management.
• Familiarity with CloudFormation for infrastructure as code.

Key Skills

Education

Not specified