Data Reliability Engineer (Hyderabad)

Job Scope: - Responsible for orchestrating, monitoring, and maintaining reliable and scalable data pipelines across Tanlas CPaaS ecosystem. - Ensure observability, reliability, and data quality across all data platforms through monitoring, alerting, and automated health checks. - Participate in incident detection, troubleshooting, and resolution to minimize downtime and data disruptions. - Implement and maintain data quality frameworks ensuring consistency, accuracy, and availability of business-critical data. Job Responsibilities: - Design, build, and maintain data pipeline orchestration workflows using tools like Apache Airflow or Prefect. - Implement monitoring and logging frameworks (Prometheus, Grafana, ELK, Splunk) to ensure proactive alerting and performance visibility. - Manage incidents by identifying anomalies, conducting root cause analysis, and coordinating resolutions across teams. - Enforce data quality frameworks, including validation checks, schema management, and data freshness monitoring. - Collaborate with engineering, product, and analytics teams to ensure seamless data flow and high system reliability. - Automate repetitive data operations and create runbooks for faster troubleshooting. - Document operational procedures, system health dashboards, and data reliability SLAs/SLOs. Qualification and Experience: - B.E. / B.Tech / M.Sc. / MCA in Computer Science, Information Systems, or related discipline. - 35 years of experience in Data Operations / Data Engineering / Data Reliability roles. - Proven exposure to pipeline orchestration, monitoring, troubleshooting, and data quality management in large-scale production environments. Knowledge and Skills: - Hands-on experience with orchestration tools (Apache Airflow, Prefect, or equivalent). - Strong experience in monitoring & logging using Prometheus, Grafana, ELK, or Splunk. - Knowledge of incident management and troubleshooting techniques in data environments. - Experience implementing and managing data quality frameworks. - Proficiency in SQL and scripting languages (Python, Bash). - Familiarity with cloud data environments (AWS, GCP, or Azure). - Understanding of CI/CD, version control, and automation principles. - Valuable problem-solving, analytical, and collaboration skills. Why Join Us Impactful Work: Play a pivotal role in safeguarding Tanla's assets, data, and reputation in the industry. Tremendous Growth Opportunities: Be part of a rapidly growing company in the telecom and CPaaS space, with opportunities for professional development. Innovative Environment: Work alongside a world-class team in a challenging and fun environment, where innovation is celebrated. Tanla is an equal opportunity employer. We champion diversity and are committed to creating an inclusive environment for all employees. Job Scope: - Responsible for orchestrating, monitoring, and maintaining reliable and scalable data pipelines across Tanlas CPaaS ecosystem. - Ensure observability, reliability, and data quality across all data platforms through monitoring, alerting, and automated health checks. - Participate in incident detection, troubleshooting, and resolution to minimize downtime and data disruptions. - Implement and maintain data quality frameworks ensuring consistency, accuracy, and availability of business-critical data. Job Responsibilities: - Design, build, and maintain data pipeline orchestration workflows using tools like Apache Airflow or Prefect. - Implement monitoring and logging frameworks (Prometheus, Grafana, ELK, Splunk) to ensure proactive alerting and performance visibility. - Manage incidents by identifying anomalies, conducting root cause analysis, and coordinating resolutions across teams. - Enforce data quality frameworks, including validation checks, schema management, and data freshness monitoring. - Collaborate with engineering, product, and analytics teams to ensure seamless data flow and high system reliability. - Automate repetitive data operations and create runbooks for faster troubleshooting. - Document operational procedures, system health dashboards, and data reliability SLAs/SLOs. Qualification and Experience: - B.E. / B.Tech / M.Sc. / MCA in Computer Science, Information Systems, or related discipline. - 35 years of experience in Data Operations / Data Engineering / Data Reliability roles. - Proven exposure to pipeline orchestration, monitoring, troubleshooting, and data quality management in large-scale production environments. Knowledge and Skills: - Hands-on experience with orchestration tools (Apache Airflow, Prefect, or equivalent). - Strong experience in monitoring & logging using Prometheus, Grafana, ELK, or Splunk. - Knowledge of incident management and troubleshooting techniques in data environments. - Experience implementing and managing data quality frameworks. - Proficiency in SQL and scripting languages (Python, Bash). - Familiarity with cloud data environments (AWS, GCP, or Azure). - U