Site Reliability Engineer

The Site Reliability Engineer is responsible for ensuring the high availability, reliability, and

performance of oneZero’s AWS-centric microservices platform supporting analytics and market-data

products delivered to global brokers. This role is deeply technical, requiring strong AWS expertise and

Python proficiency to automate operations, debug production services, optimize performance, and

support continuous delivery in a 24×7 financial services environment where uptime is mission-critical.

Reporting to the IT Operations Manager, this position demands independent technical decisionmaking

and the ability to exercise sound judgment when responding to critical incidents. The SRE

operates with significant autonomy in assessing system performance, diagnosing complex issues, and making critical determinations that impact service availability across a high-traffic, globally distributed infrastructure.

Responsibilities

AWS Infrastructure Monitoring and Incident Response

●      Monitor and manage AWS services supporting production workloads (ECS/EKS, EC2, Lambda, API Gateway, SQS/SNS, RDS, ElastiCache, CloudFront)

●      Respond to alerts from CloudWatch, Datadog, and custom monitoring scripts with urgency and precision

●      Exercise independent judgment in assessing incident severity and determining appropriate response strategies

●      Diagnose scaling, networking, and performance issues in distributed AWS systems

●      Perform incident response, ensuring rapid recovery and minimal downtime

●      Coordinate with development teams during critical incidents and outages, serving as the technical authority for infrastructure decisions

Python-Driven Troubleshooting and Automation

●      Write Python scripts and tools to automate operational tasks, system checks, and data validation routines.

●      Analyze Python microservice behavior by reading logs, debugging issues, and profiling performance

●      Build or enhance internal CLI tools to improve support workflows

●      Use Python to interrogate APIs, AWS resources (via boto3), and production data sources

●      Independently assess automation opportunities and implement solutions to reduce manual workload

Production Systems and Data Flow Stability

●      Maintain stability across charting engines, data ingestion pipelines, market-data feeds, scanning engines, and sentiment analysis services

●      Investigate failures in REST APIs, WebSocket streams, and asynchronous workers

●      Validate deployments and configurations for AWS-based microservices

●      Ensure data completeness and accuracy across instruments, markets, and broker-specific configurations

●      Make real-time decisions on system changes, maintenance windows, and emergency response procedures

Collaboration and Continuous Operations Improvement

●      Work with DevOps engineers to refine CI/CD pipelines, infrastructure-as-code workflows, and AWS deployment patterns

●      Collaborate with backend teams to improve microservice reliability and observability

●      Provide feedback on Python code, error-handling logic, and operational robustness

●      Contribute to post-incident root cause analyses and propose architectural or automation improvements

●      Participate in an on-call rotation to provide round-the-clock infrastructure support

●      Documentation and Runbook Management

●      Maintain detailed operational documentation, AWS service runbooks, and troubleshooting guides

●      Build automated checks and self-healing routines where feasible

●      Drive SRE best practices across the team

●      Document configurations, standards, and operational procedures that align with industry best practices

Required Skills & Experience
Experience Requirements

●      2+ years in production support, SRE, or DevOps with a strong AWS and Python footprint

●      Demonstrated ability to exercise independent judgment in high-pressure situations and make

●      critical decisions affecting system availability

●      Strong Python scripting and debugging skills (must be able to analyze stack traces, write

●      scripts, automate workflows)

●      Strong analytical mindset and exceptional problem-solving ability

●      Calm, structured communication during incidents

●      Ability to work cross-functionally with DevOps, developers, QA, and product staff

●      Keen attention to detail and strong ownership of production systems

●      Comfortable working in a high-availability, high-traffic environment

●      Off-hours support and coverage as part of on-call rotation

Technical Expertise

AWS Services:

●      ECS or EKS (service deployments, scaling behavior, debugging containers)

●      EC2, Lambda, API Gateway

●      SQS/SNS messaging patterns

●      RDS (PostgreSQL/MySQL), DynamoDB

●      S3 and CloudFront

●      IAM, KMS, networking (VPC, subnets, security groups)

Monitoring & Observability:

●      CloudWatch, Datadog, Grafana, OpenSearch/Kibana

Infrastructure & DevOps:

●      Docker containerization

●      Infrastructure-as-code (CloudFormation, Terraform)

●      CI/CD pipelines (CodePipeline, GitHub Actions, GitLab CI, or similar)

Development & Data:

●      REST APIs, WebSocket protocols, asynchronous workers, distributed system behavior

●      SQL proficiency and performance investigation for relational databases

●      MongoDB with JavaScript proficiency

Preferred Qualifications

●      Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent

●      practical experience

●      Experience in fintech, trading systems, or market-data streaming

●      Python experience with data processing, concurrency (asyncio), or task queues (Celery/RQ)

●      Exposure to Kinesis, Kafka, or other event-streaming platforms

●      Familiarity with FastAPI-based microservices

●      Experience with cost optimization and AWS Well-Architected practices

●      Understanding of foreign exchange markets and trading platform requirements

Success Profile

The ideal candidate will demonstrate:

●      Operational Excellence: Reduced production incidents and improved uptime through proactive monitoring and rapid incident response

●      Automation Focus: Faster MTTD and MTTR through automation and AWS-driven improvements

●      Technical Impact: Operational tooling and Python automation that significantly reduces manual workload

●      Collaboration: Positive feedback from internal teams and external broker partners

●      Ownership: Strong sense of accountability for production system health and reliability