Principal Engineer- Data Devops
4 weeks ago
Job Overview:
We are seeking an experienced Principal Engineer (Data DevOps) to lead our Data DevOps team in building, managing, and optimizing high-scale, secure, and reliable big data platforms. The ideal candidate will combine strong technical expertise with proven leadership skills, driving best practices in cloud infrastructure, automation, CI/CD, and big data technologies. This role involves managing cross-functional priorities, mentoring engineers, and ensuring delivery of high-quality, scalable data solutions.
Key Responsibilities:
● Lead, mentor, and grow a high-performing Data DevOps team, fostering technical excellence and ownership.
● Drive architecture, design, and implementation of large-scale cloud and data infrastructure, ensuring scalability, performance, and security.
● Collaborate closely with Data Engineering, Data Science, Analytics, and Product teams to deliver efficient and reliable data platforms.
● Oversee operations and optimization of AWS-based infrastructure, including VPC, EC2, S3, EMR, EKS, SageMaker, Lambda, CloudFront, CloudWatch, and IAM. ● Manage and scale big data platforms leveraging Kafka, Hive HMS, Apache Ranger, Apache Airflow, EMR, Spark, Trino, Looker, and Jupyter Notebooks.
● Implement and maintain CI/CD pipelines and infrastructure automation using Terraform, Ansible, and CloudFormation.
● Ensure system observability, proactive incident management, and SLA adherence.
● Champion cloud security best practices, including API security, TLS/HTTPS, and access control policies.
● Partner with stakeholders to prioritize initiatives, manage budgets, and optimize cloud and operational costs
Required Qualifications
Experience: 8+ years in DevOps/Data DevOps or related fields, including at least 4+ years in a leadership role.
● Proven track record in managing high-scale big data infrastructure and leading engineering teams.
● Strong hands-on experience with AWS services and infrastructure automation tools (Terraform, Ansible, CloudFormation).
● Deep knowledge and hands-on experience with Kafka, Hive HMS, Apache Ranger, Apache Airflow, EMR, Spark, Trino, Jupyter Notebooks, and Looker.
● Proficiency in Kubernetes/EKS, Docker, ECS, and CI/CD tools.
● Strong understanding of networking, cloud security, and compliance requirements.
● Excellent communication, stakeholder management, and decision-making skills.
● Exposure to SQL and data query optimization is an advantage.
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