Lead/Senior Lead - Data Devops
- Salary
- ₹10–20 LPA
- Location
- Noida, India
- Experience
- Senior
About the company & role
About Us: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. Job Overview: We are seeking an experienced 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.