Position: Solution Arhitect (DevOps/Back-end expertise)
Company: Data Science UA
Category: Lead
Experience required: 5y
English level: upper
Published: 2022-07-01T00:00:00+03:00

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 (Python and one of the languages: C++/Go)
✅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.

**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.