Description

Key Responsibilities
 
Reliability & Operations
•       Ensure the availability, performance, scalability, and reliability of data and intelligence platforms.
•       Manage production environments supporting data ingestion, processing, transformation, storage, analytics, and AI/ML workloads.
•       Participate in on-call rotations and incident response activities.
•       Lead troubleshooting efforts for complex production issues and drive root cause analysis (RCA).
•       Develop and implement service level indicators (SLIs), service level objectives (SLOs), and error budgets.
 
Automation & Engineering
•       Design and develop automation to improve operational efficiency and system reliability.
•       Build self-healing solutions and automate routine operational tasks.
•       Create tools and scripts to monitor, deploy, and manage large-scale distributed systems.
•       Improve deployment processes through CI/CD pipelines and Infrastructure as Code (IaC).
 
Observability & Monitoring
•       Design and maintain monitoring, logging, tracing, and alerting solutions.
•       Create dashboards and actionable alerts to proactively identify service degradation.
•       Analyze system performance metrics and recommend optimization opportunities.
•       Drive observability standards across data services and platforms.
 
Platform & Infrastructure Management
•       Support cloud-based infrastructure and platform services across Azure, AWS, or GCP environments.
•       Optimize compute, storage, networking, and data platform resources.
•       Work with containerized and Kubernetes-based workloads.
•       Ensure high availability and disaster recovery capabilities are implemented and tested.
 
Data Platform Reliability
•       Support modern data ecosystems including data lakes, warehouses, streaming platforms, and analytics environments.
•       Monitor ETL/ELT pipelines, batch processing, real-time streaming, and data orchestration services.
•       Partner with Data Engineers to improve pipeline reliability and data quality monitoring.
•       Ensure platform scalability for growing data volumes and user demands.
 
Security & Compliance
•       Implement security best practices and operational controls.
•       Support compliance requirements related to data governance and privacy.
•       Collaborate with security teams to remediate vulnerabilities and improve platform security posture.
 
Continuous Improvement
•       Conduct post-incident reviews and drive corrective and preventive actions.
•       Identify reliability risks and implement long-term improvements.
•       Promote a culture of operational excellence, resilience, and automation.
•       Contribute to engineering standards, runbooks, knowledge sharing, and best practices.
 
Required Qualifications
Education
•       Bachelor’s degree in computer science, Information Technology, Engineering, or related field, or equivalent practical experience.
Experience
•       3+ years of experience in Site Reliability Engineering, DevOps, Systems Engineering, Cloud Engineering, or a related role.
•       Experience supporting production environments with high availability requirements.
•       Experience managing cloud infrastructure and distributed systems.
 
Technical Skills
•       Strong knowledge of Linux systems administration.
•       Proficiency in one or more programming languages such as Python, Java, Go, C#, or JavaScript.
•       Experience with CI/CD tools and deployment automation.
•       Experience with Infrastructure as Code tools such as Terraform, ARM, or Bicep.
•       Experience with Kubernetes and container technologies.
•       Knowledge of monitoring and observability technologies such as Prometheus, Grafana, Datadog, Azure Monitor, Splunk, or OpenTelemetry.
•       Understanding of networking, DNS, load balancing, and distributed systems concepts.
 
Experience supporting data platforms such as:
o   Azure Data Lake
o   Azure Synapse Analytics
o   Databricks
o   Snowflake
o   Kafka
o   SQL/NoSQL databases
o   Data orchestration platforms
 
Preferred Qualifications
•       Experience supporting AI/ML platforms and MLOps environments.
•       Experience with Azure cloud-native services.
•       Familiarity with data governance and data quality frameworks.
•       Knowledge of reliability engineering best practices and SRE methodologies.
•       Experience implementing SLOs, SLIs, and error budgets.
•       Experience supporting large-scale analytics and business intelligence environments.
•       Azure, AWS, Kubernetes, Terraform, or DevOps certifications

Key Skills

Education

Bachelor's degree