Senior DataOps Engineer (AWS & Security Focused)
New
M
MinderaCloud data platforms
Workable workplace: remote; Workable locations: Bengaluru, Karnataka, IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 6+ years of professional experience in DataOps, DevOps, Data Engineering, or Cloud Platform Engineering; at least 4 years of hands-on experience with AWS.
- Required Skills
- AWSDockerPythonSQLApache AirflowKubernetesCI/CDTerraform
Requirements
- Have 6+ years of professional experience in DataOps, DevOps, Data Engineering, or Cloud Platform Engineering.
- Have at least 4 years of hands-on experience with AWS.
- Have strong experience with AWS data services, including S3, Glue, Athena, Redshift, or EMR.
- Have hands-on experience with Terraform and Infrastructure as Code.
- Understand AWS security, including IAM, KMS, VPC networking, Secrets Manager, and security best practices.
- Have experience building and maintaining CI/CD pipelines using GitHub Actions, GitLab CI, or AWS CodePipeline.
- Be proficient in Python and SQL.
- Have experience with data orchestration tools such as Apache Airflow, Amazon MWAA, or AWS Step Functions.
- Be familiar with Docker and Kubernetes.
- Have experience with logging, monitoring, auditing, and cloud security controls.
- Preferred: experience with AWS EKS, ECS, Lambda, or Kinesis; familiarity with dbt; or experience implementing automated security checks and compliance controls.
Responsibilities
- Design, deploy, and maintain scalable, highly available AWS data infrastructure.
- Use AWS data services including S3, Glue, EMR, Athena, Redshift, and Kinesis.
- Optimise infrastructure performance, reliability, and cost efficiency.
- Implement security practices across AWS infrastructure and data pipelines, including identity and access controls, encryption, secrets management, network security, and data protection.
- Use AWS GuardDuty, CloudTrail, and monitoring tools to strengthen security visibility, auditing, and compliance.
- Build and maintain infrastructure as code using Terraform and automate CI/CD pipelines.
- Containerise applications and manage containerised workloads using Docker and Kubernetes.
- Build and maintain data workflows using Apache Airflow, Amazon MWAA, or AWS Step Functions.
- Implement monitoring, logging, governance, and automated compliance checks across data workflows.
- Troubleshoot infrastructure bottlenecks and data platform reliability issues, and improve automation, security, and operational efficiency.
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