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We are seeking a highly skilled Cloud DevOps & Data Platform Engineer with strong expertise in DevOps, cloud platforms, data analytics, and database systems. This role will be responsible for building, automating, monitoring, and optimizing cloud-based infrastructure and data platforms while supporting business intelligence and data-driven decision-making.
Job Responsibility:
Design, implement, and maintain CI/CD pipelines and cloud infrastructure using DevOps best practices
Manage and optimize GCP cloud services, ensuring high availability, scalability, and cost efficiency
Develop, deploy, and monitor applications and services on Linux-based systems
Support and enhance Power BI dashboards, datasets, and data models for business reporting
Write, optimize, and maintain PL/SQL queries, procedures, and database objects
Perform database administration tasks related to DBMS performance, tuning, and reliability
Develop automation scripts and utilities using Python for infrastructure and data workflows
Implement monitoring, logging, and alerting for infrastructure and applications
Ensure security, access control, and compliance across cloud and data platforms
Collaborate with engineering, analytics, and business teams to deliver scalable solutions
Requirements:
Strong experience in DevOps tools and practices (CI/CD, automation, monitoring)
Hands-on experience with Google Cloud Platform (GCP)
Proficiency in Linux system administration
Solid expertise in Power BI (reports, dashboards, DAX, data modeling)
Strong knowledge of PL/SQL and relational DBMS concepts
Experience with Python scripting for automation and data processing
Understanding of cloud security, IAM, and networking concepts
Experience working in Agile / DevOps environments
3+ Year Experience
Availability for night shifts as needed to support global teams
Flexible to work during us time to support customers
Flexibility in working hours and the ability to adapt to varying schedules is essential
Nice to have:
Experience with containerization and orchestration (Docker, Kubernetes)
Exposure to data pipelines and ETL processes
Familiarity with infrastructure-as-code tools (Terraform, Deployment Manager)