Cleared AWS Developer, Full Scope Polygraph
VPS
AWSCloudDockerJavaScriptKubernetesPythonTerraformTypeScript
Manager, Data Engineering
Quanata
full-time
Posted on:
Origin: • 🇺🇸 United States • California, Rhode Island
Visit company websiteSalary
💰 $315,000 - $380,000 per year
Job Level
Mid-LevelSenior
Tech Stack
AWSCloudDockerETLKubernetesPythonTerraform
About the role
- Lead, mentor, and grow a high-performing team of Data Engineers, fostering a culture of engineering excellence, innovation, and cross-functional collaboration
- Drive the team's design and implementation of automated CI/CD/CT pipelines and ETL/ELT processes to accelerate the entire model lifecycle, from data validation and training to production deployment and monitoring
- Establish Data Engineering best practices to ensure data accuracy, consistency, security, and adherence to governance frameworks
- Monitor the performance of data systems and implement improvements to enhance efficiency and reduce latency
- Partner with key stakeholders, data analysts and business leaders to define platform requirements, drive adoption, and ensure the DE team delivers measurable business value
- Oversee the integration of security controls (DevSecOps) throughout the data engineering lifecycle, including data encryption, access management, and vulnerability scanning to protect sensitive data and meet industry standards
Requirements
- BS degree in Computer Science, engineering or related field or equivalent relevant experience
- 6-8 years of professional experience in data management, software engineering, or DevOps engineering
- Proven leadership experience with a track record of managing and developing technical teams
- Excellent communication and stakeholder management skills
- Deep, hands-on expertise with Infrastructure as Code (IaC) using Terraform
- Container orchestration with Kubernetes and Docker in production environments
- Extended experience working in cloud-native environment with strong preference toward AWS
- Strong programming skills in Python
- Solid understanding of the end-to-end machine learning lifecycle
- Problem-Solving: Ability to resolve complex data architecture challenges and drive technical roadmaps
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