Senior Devops Engineer

Role & responsibilities

DevOps Engineer

AWS DevOps services

Key Responsibilities

1. CI/CD Pipeline Management

• Design, implement, and maintain

  end-to-end CI/CD pipelines

   for continuous integration, testing, and deployment of data and application workloads.
• Integrate and automate workflows using

  AWS CodePipeline, CodeBuild, CodeDeploy, and Jenkins

  , ensuring zero-downtime deployments.

2. Infrastructure Automation & Provisioning

• Build and manage

  Infrastructure as Code (IaC)

   using

  Terraform, CloudFormation, or Ansible

   to automate the provisioning of AWS services and data environments.
• Implement

  auto-scaling, backup, and disaster recovery

   strategies for high availability and resilience.

3. Cloud & Data Production Management

• Deploy and manage

  Data Production environments

   on AWS, ensuring system reliability, data consistency, and minimal downtime during releases.
• Collaborate with data engineering teams to operationalize and optimize

  ETL/ELT pipelines

  ,

  Spark clusters

  ,

  AWS Glue jobs

  , and

  Iceberg tables

  .
• Manage

  production-grade Data Lakes and Lakehouses

   using

  S3, EMR, Glue, Redshift, Athena, and Lake Formation

  .
• Monitor and troubleshoot production issues using

  CloudWatch, CloudTrail, Prometheus, or Grafana

  .

4. Containerization & Orchestration

• Containerize and deploy applications using

  Docker and Kubernetes (EKS)

   for scalable and consistent environment management.
• Manage Helm charts and Kubernetes manifests for

  multi-environment deployments

   (Dev, QA, UAT, Prod).

5. Collaboration & Continuous Improvement

• Work cross-functionally with developers, QA, and data engineers to

  improve deployment efficiency

   and

  enhance platform reliability

  .
• Evaluate new tools and techniques to

  strengthen automation, observability, and security

   within the data and DevOps ecosystem.

Preferred candidate profile

• Bachelors/Master’s degree

   in Computer Science, Information Technology, or a related discipline.

• Lead - 8–10 years

   of hands-on experience in

  DevOps engineering

  , with strong exposure to

  data infrastructure and production environments

  .

• Engineer - 6–8 years

   of hands-on experience in

  DevOps engineering

  , with strong exposure to

  data infrastructure and production environments

  .
• Proven experience managing

  AWS-based Data Platforms and Data Lakes

  , including

  S3, Glue, EMR, Redshift, Lake Formation, and Athena

  .
• Strong understanding of

  Data Lake implementations

  ,

  Medallion Architecture (Bronze–Silver–Gold)

  , and

  data lineage/governance principles

  .
• Expertise in

  AWS services

   such as

  EC2, CloudFormation, CloudWatch, CloudTrail, CodePipeline, CodeBuild, and CodeDeploy

  .
• Strong proficiency in

  Infrastructure as Code (IaC)

   tools like

  Terraform

   and

  CloudFormation

  .
• Experience with

  Docker, Kubernetes (EKS)

  , and

  container orchestration

   for scalable data workloads.
• Scripting experience in

  Python, Bash/Shell, or Ruby

   for automation, deployment, and monitoring.
• Deep understanding of

  CI/CD pipelines

   and

  Git-based workflows

  .
• Hands-on experience in

  Data Production deployment, release management

  , and

  root cause analysis

   in real-world environments.
• Familiarity with

  Apache Spark

  ,

  AWS Glue

  , and

  Iceberg

   preferred.
• Strong analytical, troubleshooting, and communication skills with the ability to

  engage directly with clients

   to identify and mitigate risks in infrastructure or deployment.