Chief Engineer

Role Overview

Lead the design and build of the enterprise data platform with a strong product mindset, focusing on scalable, real-time and batch data capabilities. Drive the architecture and implementation of streaming data platforms to enable low-latency data use cases across the enterprise.

What You Will Do

Design, implement, and maintain scalable and reliable data and analytics infrastructure on AWS + Snowflake. Develop and support tools for the end-to-end data lifecycle, including data ingestion, model deployment, and monitoring, with an emphasis on automation and DevSecOps.

Why It Might Be a Fit

Hands-on experience with AWS services, experience in building and scaling cloud infrastructure for machine learning use cases, solid understanding of the ML lifecycle, proficient scripting and automation skills in Bash and Python, experience with Infrastructure-as-Code tools, and proficiency with version control systems.

Requirements

• Hands-on experience with AWS services such as EC2, ECS, S3, Lambda, Step Functions, RDS, DynamoDB, IAM, VPC, Route 53, and CloudWatch.
• Experience with AWS & Snowflake services such as SageMaker, AWS Glue, Amazon EMR, and Airflow.
• Experience in building and scaling cloud infrastructure for machine learning use cases.
• Solid understanding of the ML lifecycle: data preprocessing, feature engineering, model training, evaluation, and deployment.
• Proficient scripting and automation skills in Bash and Python.
• Experience with Infrastructure-as-Code tools, especially AWS CloudFormation.
• Proficiency with version control systems such as GitHub and GitHub Actions.
• Familiarity with monitoring and observability tools like Grafana and Prometheus, as well as engineering tools such as Artifactory, Snyk, and Docker.
• Comfortable working across the full software lifecycle: design, build, change, and run.
• Strong communication skills and a commitment to inclusivity and continuous improvement.

Benefits

• We're keen to support you with the next step in your career.