Senior DevOps Engineeer
Description
We are looking for a Senior DevOps Engineer with strong expertise in AWS and Python to join our growing engineering team. The ideal candidate will play a key role in building, automating, and maintaining cloud infrastructure and deployment pipelines, ensuring high availability and performance of data-driven applications.
Responsibilities:
- Architect and manage scalable, secure, and cost-efficient AWS infrastructure for data platforms.
- Design and maintain CI/CD pipelines for seamless data engineering workflows and application deployments.
- Develop automation solutions using Python and Shell scripting to streamline data platform operations.
- Collaborate with stakeholders, data engineers, and application teams for smooth delivery and operations.
- Containerise and manage services using Docker across environments.
- Implement Infrastructure as Code (IaC) for consistent and version-controlled deployments.
- Support and optimise large-scale data platforms (like Spark and Hadoop).
- Build and maintain observability frameworks (monitoring, logging, tracing) for data pipelines and distributed systems
- Troubleshoot infrastructure and data pipeline issues to ensure high availability.
- Ensure system performance, security, and reliability across cloud environments.
- Optimise cloud resource utilisation and cost efficiency, especially for large-scale data workloads.
- Drive incident management, RCA, and continuous improvement.
- Stay updated with DevOps, cloud, and data engineering best practices and drive adoption within the team.
Requirements:
- BE / B. Tech in Computer Science or a related field.
- 5-7 years of experience in DevOps or cloud engineering.
- Strong hands-on experience with AWS services (EC2, S3, RDS, Lambda, DynamoDB, CloudFormation, etc. )
- Proficiency in Python.
- Good knowledge and experience with Linux systems and Shell scripting.
- Hands-on experience with Docker.
- Understanding of CI/CD tools and DevOps practices.
- Strong debugging and troubleshooting skills.
- Knowledge of observability tools (e. g., Prometheus, Grafana, ELK stack).
- Experience with Infrastructure as Code tools like Terraform or CloudFormation.
- Exposure to Kubernetes or container orchestration.
- Experience working with data platforms or big data ecosystems.
- Strong communication and collaboration abilities.
- Self-driven with a passion for automation and continuous improvement.
- AWS Certification (e. g., AWS Certified Solutions Architect / DevOps Engineer) is a plus.