DevOps Engineer (CPT In Office) at Datafin Recruitment

ENVIRONMENT:

• A DevOps Engineer with a security-first mindset who is passionate about building scalable, reliable systems is wanted to join the team of a cutting-edge global FinTech company committed to delivering funding products to small-to-medium sized businesses. This is a role for someone who takes genuine ownership — running projects end to end and delivering meaningful improvements to our infrastructure, tooling, and engineering maturity.
• The successful incumbent must possess a Bachelor’s Degree in Computer Science/Software Engineer or similar field with a minimum of 3-5 years’ experience in DevOps, Platform, or Infrastructure Engineering including ands-on experience with AWS across serverless and containerised workloads (including Docker), e.g. Lambda, ECS, and API Gateway.

DUTIES:

Infrastructure & Delivery –

• Design, build, and maintain CI/CD pipelines (CircleCI) to automate and streamline software delivery.
• Provision and manage AWS infrastructure as code (e.g. Terraform), designing containerised and serverless architectures (Lambda, ECS, API Gateway) across multi-account environments that scale with traffic and a growing team.

Reliability & Security –

• Implement and maintain monitoring, logging, and alerting (e.g. CloudWatch, New Relic), and troubleshooting issues across infrastructure, deployments, and application performance.
• Apply a security-first approach — secure defaults, least privilege, threat-aware thinking — and work with cloud security and scanning tooling (Cloudflare, Aikido) to strengthen the platform’s posture.
• Be available on call during peak or product launch periods when required.

Platform, Collaboration & Ownership –

• Provide day-to-day operations and infrastructure support and build internal tooling and platform capabilities to Support Engineers as the team grows.
• Administer third-party service-provider instances and integrations (e.g. Zoho CRM, Slack, n8n) and endpoint/identity tooling (Microsoft Entra ID, Intune) where they intersect with developer experience and security.
• Take ownership of DevOps and security projects, running them end to end, while guiding Engineers and championing an AI-forward approach to raise productivity and quality.
• Document processes, procedures, and configurations to ensure consistency and repeatability.

REQUIREMENTS:

Qualifications –

• Bachelor’s Degree in Computer Science, Software Engineering, or a related field (or equivalent practical experience).

​​​​​​​Experience/Skills –

• 3-5 Years of experience in DevOps, Platform, or Infrastructure Engineering.
• Hands-on experience with AWS across serverless and containerised workloads (including Docker), e.g. Lambda, ECS, and API Gateway.
• Proven experience building CI/CD pipelines to automate software delivery (They use CircleCI; similar tooling is fine).
• Experience with Infrastructure as Code — Terraform preferred (equivalent tools such as CloudFormation are fine).
• Proficiency in scripting languages such as Python and Bash.
• Experience with Git-based source control (e.g. GitHub).
• Strong understanding of networking, security, and system administration concepts.

​​​​​​​Preferred to haves –

• DevSecOps experience, embedding security throughout the development and deployment lifecycle.
• Exposure to security and compliance frameworks such as ISO 27001, Cyber Essentials, DORA, or GDPR.
• Platform Engineering experience — building self-service tooling, reusable IaC modules, or paved-road workflows for other Engineers.
• Experience administering endpoint, identity, and security tooling (e.g. Microsoft Entra ID, Intune, Cloudflare, Aikido) and managing third-party service-provider instances (e.g. Zoho CRM, Slack, n8n).
• Experience with observability tooling and managed relational databases (e.g. CloudWatch, New Relic, RDS Aurora / PostgreSQL).
• Experience working in a regulated FinTech or Financial Services environment.

ATTRIBUTES:

• A security-first mindset: secure defaults, least privilege, and threat-aware design.
• Genuine comfort and proficiency using AI tools in day-to-day Engineering work, with an AI-forward mindset.