Experience: 5.00 + years

Salary: Confidential (based on experience)

Shift: (GMT+05:30) Asia/Kolkata (IST)

Opportunity Type: Remote

Placement Type: Full time Permanent Position

(*Note: This is a requirement for one of Uplers' client - Bidgely)

What do you need for this opportunity?

Must have skills required:

Monitoring tools, automation, Kubernetes, Docker/Kubernetes, Grafana, ELK, Splunk tool, Datadog

Bidgely is Looking for:

Key Responsibilities:

• System Reliability and Uptime:
• Ensure high availability and performance of critical systems, APIs, and infrastructure components.
• Define and track Service Level Objectives (SLOs) and Service Level Indicators (SLIs) to maintain system reliability standards.
• Develop and maintain error budgets to balance new feature development with reliability.
• Real-Time Monitoring and Alerting:
• Implement and maintain comprehensive monitoring and alerting solutions across critical services, such as APIs, data processing pipelines, databases (e.g., Cassandra, Redshift), and cloud infrastructure.
• Set up proactive monitoring for API latency, system load, throughput, and error rates to identify issues before they impact customers.
• Collaborate with DevOps and Platform & Infra teams to create end-to-end observability for the entire data processing ecosystem.
• Incident Management and Root Cause Analysis:
• Act as the first responder to high-severity incidents, taking ownership of incident
• management and response.
• Conduct thorough root cause analysis post-incident, working closely with cross-functional teams to implement long-term resolutions.
• Develop incident runbooks and playbooks to streamline incident response and reduce Mean Time to Recovery (MTTR).
• Automation of Toil and Operational Efficiency:
• Identify and automate repetitive, manual tasks to minimize operational overhead,
• particularly within data ingestion, disaggregation, and notification workflows.
• Implement self-healing solutions for commonly recurring issues, reducing the need for manual intervention.
• Enhance operational efficiency by optimizing resource utilization across infrastructure components like EMR clusters, Redis instances, and SQS queues.
• Capacity Planning and Scalability:
• Perform regular capacity planning to ensure our systems can handle future growth
• and data processing needs, especially during peak usage periods.
• Collaborate with the Platform & Infra and DevOps teams to scale infrastructure effectively, ensuring we meet SLAs for data processing and customer response times.
• Monitor and optimize infrastructure costs by ensuring efficient resource allocation and cloud utilization.
• Performance Optimization:
• Continuously monitor system performance and optimize APIs, databases, and
• backend services to reduce latency and improve response times.
• Address performance bottlenecks in the data processing pipeline to ensure timely aggregation, disaggregation, and notification generation.
• Develop strategies to improve the accuracy and quality of data insights provided to customers.
• Documentation and Cross-Team Collaboration:
• Document all reliability processes, runbooks, and incident resolution steps to
• maintain clear, actionable resources for the team.
• Work closely with Product Support to ensure that customer-impacting issues are resolved quickly, and with DevOps to streamline the deployment and release processes.
• Collaborate on building a culture of reliability and efficiency across the organization.
  
  
  

Key Performance Indicators (KPIs):

• Service Uptime and Availability: Percentage uptime for critical services and systems.
• Mean Time to Recovery (MTTR): Average time to resolve incidents and restore services.
• Incident Frequency: Number of incidents and issues per period, aiming for continuous reduction.
• Error Budget Compliance: Adherence to error budgets without breaching SLOs.
• Automation Coverage: Percentage of manual tasks that have been automated to reduce operational workload.
• Latency and Performance Metrics: API latency (P50, P95, P99) and system throughput for key workflows.
  
  
  

Qualifications:

• B.Tech/Bachelor in Computer Science or a related field (math, physics, engineering)
• 3-7 years of experience in Site Reliability Engineering (SRE), DevOps, or Infrastructure Engineering.
• Strong experience with monitoring and observability tools (e.g., Prometheus, Grafana, Datadog, ELK stack).
• Proficiency in automation and scripting (e.g., Python, Bash, Terraform) to manage infrastructure as code and automate repetitive tasks.
• Hands-on experience with cloud platforms (AWS preferred) and knowledge of services like EC2, SQS, EKS, S3, RDS, Redshift, EMR.
• Experience with incident management and root cause analysis methodologies.
• Familiarity with database systems (e.g., Cassandra, Redis, MySQL) and large-scale data processing pipelines.
• Excellent problem-solving skills, with a proactive approach to identifying and resolving issues.
• Proficient in SQL (Basic and Advanced) to be able to analyze error and log data and identify pattern to reduce # of recurring issues or identify top opportunity areas to reduce ticket volume.
• Bonus point if he is aware of any reporting tool like Tableau/Power BI /Looker etc
  
  
  

How to apply for this opportunity?

• Step 1: Click On Apply! And Register or Login on our portal.
• Step 2: Complete the Screening Form & Upload updated Resume
• Step 3: Increase your chances to get shortlisted & meet the client for the Interview!
  
  
  

About Uplers:

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