We are Data Science UA and we are helping one of our client to scale team for their great product. We are looking for a Solution Architect who will be the engineering owner of real-time trading and research infrastructure. Every day algorithms process more than 500 million data points. As a result, low latency and fault tolerance are essential. We are looking for a professional passionate about financial markets and algorithmic trading who will lead client`s team of developers in maintaining and improving the existing IT infrastructure. This position involves possible progression to the CTO of the project and trading profit sharing.
Responsibilities:
- Get a deep understanding of current architecture and generate an improvement plan.
- Lead the team of backend developers and data engineers.
- Ensure infrastructure and services design is highly available, scalable and fault-tolerant.
- Define operations requirements and guidelines for new services.
- Implement zero downtime and canary deployment strategies for trading applications.
- Review and design CI/CD pipelines.
- Design and plan disaster recovery architecture.
- Capacity planning and autoscaling.
- Ensure services have good observability and operability: monitoring/logging/distributed transactions tracing.
- Take an active part in decision-making regarding further architecture development.
- Continuously improve quality of service and internal culture
- Prepare solution documents with architecture and infrastructure diagrams
Required skills:
- 5+ years in software development.
- Exceptional communication skills are a must.
- Experience with cloud technologies (AWS).
- 2+ years of leading/management experience.
- 3+ years as an architect.
- Broad experience working with high-load systems.
- Experience working with streaming data processing pipelines.
Hands-on experience in Python and one of the languages: C++/Go.
Strong experience with:
- Kubernetes and its ecosystem: Helm, Docker, Argocd.
- Infrastructure as a code tool: Terraform.
- Message brokers: Apache Kafka/Redpanda.
- SQL database: ClickHouse, PostgreSQL.
- Linux (CentOS/Ubuntu) and CLI tools: bash, sed, awk, sysctl.
- Networking: TCP/IP, DNS, Firewalls, load balancers (Nginx/f5).
- Security principles and best practices.
- Configuration management tools (Ansible).
- CI/CD tools (GitLab Artifactory, Jenkins).
- Cloud providers: AWS, GCP.
- Orchestration platforms: Kubernetes.
- Data processing principles and techniques (asynchronous, parallel, batch processing).
- ETL Engineering
Experience with:
- Monitoring and logging systems: Grafana, Prometheus, Elastic Stack, Splunk, Jaeger.
- Containerization-related management stacks like Docker, Swarm, and Kubernetes.
- Microservices architecture, REST APIs & API Gateways principles and patterns.
Experience in
- Transforming existing products.
- Developing microservice platforms.
- Technical/engineering background or engineering education.
- Management and delivery of complex integrations and infrastructure projects
Background in
- Software Development, DevSecOps, Site Reliability, and/or Systems Engineering.
- Building and deploying solutions as containers on a cloud platform using an automated CI / CD pipeline.
- Configuring, monitoring, and handling scaling infrastructure in the cloud.
- Real-time observability solutions that provide visibility into system health.