Jobs / MONY Group
Cloud Platform Engineer
MONY Group · London, ENG, United Kingdom
London, ENG, United KingdomHybrid
Remuneration
Not specified
Location
London, ENG, United Kingdom
Visa sponsorship
Not specified
Job summary
This is a hands-on engineering role within the MONY Group Data Team, focusing on building and evolving a reliable data platform that supports analytics, CRM, financial reporting, and machine learning. The role involves improving engineering workflows with AI and automation, contributing to platform infrastructure, and enabling the wider team through knowledge sharing and mentorship.
Benefits
Up to 27 holidays + bank holidaysPension up to 6% employer contributionBonus schemeDigital Doctor on demandWork from anywhere scheme – 2 weeks per yearFinancial coachingMental health platform accessMentorshipTrainingOpportunities to expand skill setLinkedIn Learning license
Qualifications
- Strong software or data engineering fundamentals, including production Python and SQL
- Experience building, operating, or improving cloud-based systems
- Familiarity with infrastructure-as-code, CI/CD, version control, and automated testing
- Ability to reason about reliability, security, observability, and operational support
- Experience working with technical and non-technical stakeholders and communicating clearly
- Curiosity about AI-assisted engineering and automation, with an interest in applying these tools to practical delivery workflows
- Experience with GCP, AWS, or Azure services such as serverless runtimes, networking, data warehouses, streaming systems, or managed workflow platforms
- Experience building or configuring AI agent workflows, custom agents, tool/function calling, MCP servers, local coding-agent instructions, hooks, or SDKs
- Experience with BDD/TDD, design-for-testing, or improving testability in data and platform systems
Responsibilities
- Contribute to the design, delivery, and operation of platform infrastructure using infrastructure-as-code, primarily Terraform
- Improve CI/CD pipelines, deployment practices, and platform tooling to enable data teams to self-serve safely
- Work with security, compliance, and data protection colleagues to reduce risk and improve data handling practices
- Build robust, scalable data solutions that support business needs such as CRM, SEO, financial reporting, and personalization
- Stay close to the business context and apply software engineering practices to solve specific data problems
- Improve monitoring, alerting, data quality checks, and observability for quick issue detection and understanding
- Identify repeated or high-friction engineering tasks and automate them into reliable or AI-assisted workflows
- Help shape team practices for coding agents, prompts, local instructions, skills, hooks, and tool integrations where they deliver value
- Balance speed with security, reviewability, and maintainability when introducing AI-assisted delivery patterns
- Share practical learning through documentation, demos, pairing, and show-and-tell sessions
- Support junior team members through coaching, code review, and clear engineering standards
- Keep an informed view of the fast-moving AI tooling landscape and recommend adoption where it solves team problems
Skills
AWSAzureGCPPythonTerraform
Languages
PythonSQL
Relocation
No