Description

You will build and maintain large-scale data pipelines and machine learning infrastructure in production.

Responsibilities

• Build high-quality, low-latency, cost-effective data pipelines for ingesting internal and external data.
• Implement processes for data wrangling, assimilation, and standardization in production environments.
• Deploy, fine-tune, and execute machine learning models in production.
• Develop end-to-end data and computing infrastructure for large-scale product operations.
• Collaborate with internal stakeholders and operation units to deliver analytics capabilities and solutions.

Required Skills

• 5+ years of experience in data and machine learning production.
• Proficiency in Python, PySpark, and SQL.
• Hands-on experience with shell scripting and code versioning using GitHub.
• Experience with automation and workflow orchestration tools including Ansible, SLURM, Airflow, and Terraform.
• Strong understanding of data structures, algorithms, and ETL processing.
• Experience with cloud-based technologies, specifically data warehousing and integration in AWS.
• Ability to perform debugging, code reading, and structured programming.
• Capability to communicate technical challenges and solutions in business terms.

Preferred Skills

• Master's degree in a technical field, Computer Science, Information Technology, or Business Management.

Key Skills

Education

Master’s degree