Responsibilities 

Reliability and Performance 

• Ensure the high availability, reliability, and performance of production systems and services 

• Implement and maintain disaster recovery plans and procedures 

• Monitor and manage system health using metrics, logs, and tracing to proactively identify and resolve issues 

Automation and Infrastructure: 

• Automate repetitive tasks, including deployment, scaling, monitoring, and remediation of systems 

• Build and maintain infrastructure as code (IaC) using tools like Terraform, CloudFormation, or similar 

Incident Management 

• Participate in incident response and troubleshooting efforts to minimize downtime and resolve issues quickly 

• Conduct root cause analysis for system failures and implement preventive measures to avoid future incidents 

• Respond to incidents, perform root cause analysis, and implement solutions to prevent recurrence 

• Maintain incident response playbooks and ensure efficient on-call rotations 

Observability and Monitoring 

• Design and implement monitoring solutions using tools like Prometheus, Grafana, Datadog, or similar 

• Define and track SLIs, SLOs, and SLAs to measure and improve system performance 

Collaboration 

• Work closely with development, QA, and operations teams to ensure smooth delivery of applications 

• Act as a bridge between software engineering and operations, advocating for DevOps best practices 

• Document system configurations, processes, and procedures to ensure knowledge sharing and maintain system integrity 

Capacity and Scalability 

• Conduct capacity planning and optimize system scalability to meet future demands 

• Implement strategies for horizontal and vertical scaling of applications 

Security and Compliance 

• Ensure infrastructure security by implementing best practices and addressing vulnerabilities 

• Collaborate with the security team to meet compliance standards and audits 

Data Engineering & Automation 

• Design, develop, and maintain scalable and efficient data pipelines 

• Automate data workflows for ETL/ELT processes, integrating data from various sources into data warehouses and other storage solutions 

• Develop and maintain solutions for data transformation, data modelling, and automate the orchestration of data processing 

Data Warehouse Management 

• Design, implement, and maintain modern data warehouse architectures, ensuring effective data storage, retrieval, and accessibility 

• Work with cloud-based data warehouses (e.g., BigQuery, Snowflake, Redshift) and optimize data models for analytics and reporting 

• Develop and manage dimensional models, star/snowflake schemas, and data marts for operational and analytical use cases 

Real-time and Batch Data Processing 

• Build and manage real-time and batch data pipelines for high-volume data ingestion, processing, and analytics 

• Leverage technologies such as Apache Kafka, Apache Beam, Apache Spark, and Google Cloud Dataflow for streaming and batch processing 

Qualifications 

Experience 

• 8+ years of experience in a Data Platform including Site Reliability Engineering, DevOps, or Systems Engineering role 

Technical Skills 

• Strong programming skills in languages such as Python, Java, or similar 

• Experience in developing Data ingestion pipelines, Governance, Quality and automation 

• Proficiency in cloud platforms such as Google Cloud (Mandatory), AWS, Azure 

• Experience in leveraging AI/ML models to enhance efficiency in da Official notification