#vacancy #вакансия #devops #fintech #dataops #fulltime #remote
Devops engineer (Data)
Формат: remote
Оформление: b2b
Занятость: full-time
Английский: B2+
We’re looking for a DevOps Engineer (Data Focus) to strengthen our Data Engineering team.
This role is all about building and maintaining reliable, scalable, and observable data infrastructure that powers our trading research and production systems.
Responsibilities
• Design, implement, and maintain DevOps tooling for data pipelines and data platforms.
• Support and automate ETL workflows (e.g. Spark, Airflow).
• Build and manage monitoring and observability for data quality (DBT), data pipelines, and storage systems.
• Implement and maintain data storage infrastructure on AWS (S3, EC2, networking).
• Integrate and support Project Nessie as a transactional catalog for Data Lakes with Git-like semantics.
• Work closely with Data Engineers to ensure smooth deployment, versioning, and scaling of data jobs and pipelines.
• Automate deployment and CI/CD processes with GitLab CI/CD.
• Ensure security best practices for sensitive data handling.
• Write infrastructure automation using Python/Bash/Ansible.
• Document systems, pipelines, and DevOps processes.
Qualifications
• 5+ years in a DevOps / IT Ops / DataOps role, with hands-on experience in data-related infrastructure.
• Strong Linux knowledge (networking, kernel tuning, performance optimization).
• Hands-on experience with Airflow, ClickHouse, DBT, Spark, and Project Nessie.
• Solid knowledge of AWS services (S3, EC2, IAM, networking).
• Proficiency in scripting and automation (Python, Bash, Ansible).
• Experience with CI/CD pipelines (GitLab).
• Experience with monitoring stacks (Prometheus, Grafana, ELK).
• Familiarity with containerization and orchestration (Docker, Kubernetes).
• Understanding of data governance concepts.
• Strong communication skills and a proactive, ownership-driven mindset.
Nice-to-Have
• Experience with real-time data streaming.
• Knowledge of infrastructure as code (Terraform).
• Familiarity with security in data engineering (IAM, encryption, access control).
• Background in high-performance systems or trading environments.