Senior Data Engineer, Predictive Modeling

What you'll do

• Refactor and productionalize Python code from data scientists into reliable, maintainable applications with proper testing and documentation.
• Design, architect, and maintain scalable predictive modeling data pipelines across the company's data science ecosystem.
• Develop internal tools to increase productivity for analysts, data scientists, and other engineers.
• Build and deploy RESTful services in collaboration with software engineers and data scientists.
• Create robust ETL/ELT processes to integrate data between different systems while ensuring quality and lineage tracking.
• Design both relational and non-relational data models optimized for performance, cost, and maintainability.
• Develop high-availability applications using Docker and Kubernetes with a focus on scalability and observability.
• Mentor junior engineers and provide technical guidance on software engineering practices and data architecture.

What we're looking for

• Bachelor's degree in Computer Science, Engineering, Applied Math, Hard Sciences, or a similar field from an accredited institution.
• 5+ years of experience in data engineering and data warehousing.
• 2+ years of experience building production systems designed for scalability, availability, and robustness.
• Strong coding and application development skills in Python.
• Proficiency in SQL and NoSQL databases with knowledge of data modeling and optimization techniques.
• Experience with at least one cloud service platform provider such as AWS, GCP, or Azure.
• Expertise in container orchestration (Docker, Kubernetes), CI/CD pipelines, and version control systems like Git.
• Ability to read, write, speak, and understand English.