Description

You will design and maintain data architecture and ETL processes within an AWS environment. You own the full lifecycle of data solutions, from ingestion to warehousing.

Responsibilities

• Build and maintain ETL pipelines for large datasets using AWS Glue, EMR, Kinesis, or Kafka.
• Develop data solutions using Python, Spark, or PySpark and integrate with various APIs.
• Write and tune complex SQL queries for AWS Redshift and RDBMS like MS SQL Server or Postgres.
• Manage cloud orchestration using AWS Lambda, Event Bridge, Step Functions, SNS, and SQS.
• Implement dimension modeling and data warehousing best practices.

Required Skills

• 9+ years of experience in data engineering, data warehousing, and dimension modeling.
• Proficiency in Python development and Spark or PySpark.
• Strong SQL skills with experience in performance tuning for Redshift or other RDBMS.
• Hands-on experience with AWS Glue, EMR, Kinesis, or Kafka.
• Experience with AWS Lambda, Event Bridge, Step Functions, SNS, and SQS.
• Practical understanding of IAM Roles and Policies.
• Bachelor's degree or equivalent graduate level education.

Preferred Skills

• Experience with workflow management tools like Airflow.
• Familiarity with Infrastructure as Code using CloudFormation.
• Experience working with CI/CD pipelines and agile methodologies.

Key Skills

Education

ANY GRADUATE