DataOps Engineer - Google Cloud Platform

Location : Hyderabad, India

Experience : 5+ Years

Employment Type : Full Time

Role Overview :

Build, scale, and operate reliable cloud-based data platforms. Enable faster delivery of high-quality data products through automation and DataOps practices. Work at the intersection of Data Engineering and DevOps to improve platform reliability and efficiency.

Key Responsibilities :

- Design, build, and maintain scalable data infrastructure on GCP and AWS.

- Develop and manage Infrastructure-as-Code using Terraform.

- Build and maintain CI/CD pipelines for data platforms and workloads.

- Support deployment of data pipelines, dbt models, and orchestration workflows.

- Implement monitoring, logging, and alerting for data pipelines and infrastructure.

- Ensure security, compliance, and governance across data platforms.

- Optimize cloud resource utilization and data platform costs.

- Collaborate with data engineering, analytics, and data science teams.

- Maintain documentation, runbooks, and operational processes.

- Drive continuous improvements in platform reliability and developer experience.

Key Result Areas :

- High availability and stability of data pipelines and platforms.

- Reduced deployment failures and faster release cycles.

- Improved observability and proactive incident detection.

- Automation-driven reduction in manual operational effort. Secure and compliant data infrastructure.

- Optimized cloud costs and improved cost visibility.

- Improved productivity of data engineering and analytics teams.

Required Skillsets :

- Strong experience with Google Cloud Platform services.

- Hands-on expertise with BigQuery, Cloud Storage, Pub/Sub, Dataflow, and Cloud Composer.

- Experience with AWS data services such as Glue, Redshift, or Lambda.

- Proficiency in Terraform for multi-cloud infrastructure management.

- Experience with CI/CD tools such as GitHub Actions and Jenkins.

- Working knowledge of data platforms like BigQuery, Snowflake, or Databricks.

- Experience with monitoring and observability tools such as Prometheus and Grafana.

- Strong scripting skills in Python and Bash.

- Experience with Docker and Kubernetes or GKE.

- Familiarity with dbt and workflow orchestration tools like Airflow.

- Understanding of data security, governance, and compliance best practices.

- Experience working in Agile development environments.

Qualifications :

- 5+ years of experience in Data Engineering, DataOps, DevOps, or Platform Engineering roles.

- Experience supporting enterprise-scale data platforms preferred.