Description

You will build and optimize data pipelines and storage solutions within distributed computing environments.

This role is on-site.

Responsibilities

• Implement and tune Hadoop and Spark workloads to ensure optimal performance.
• Deploy AWS services across distributed enterprise environments, specifically using Amazon EMR.
• Design and manage data storage patterns including data lakes and data warehousing.
• Write automated unit, integration, regression, performance, and acceptance tests for data workflows.

Required Skills

• 5+ years of experience developing with Python and SQL.
• 3+ years of hands-on experience implementing and tuning Hadoop and Spark.
• Direct experience with Amazon Elastic Map Reduce (EMR).
• Proficiency in Postgres or Snowflake.
• Strong understanding of data warehousing and data lake patterns.
• Experience implementing AWS services in distributed computing environments.
• Ability to work with structured and unstructured data across various database systems.

Preferred Skills

• Bachelor’s degree in Computer Science, Data Science, or a related field, or equivalent work experience.

Key Skills

Education

Any Graduate