Cloud Engineer

• Deliver Marketing Cloud solutions end to end, from requirements and solution design through build, integration, support, and optimisation
• Build, test, and deploy multi-channel campaigns
• Design and build multi-step customer journeys in Journey Builder
• Develop dynamic, personalised emails, landing pages, and CloudPages using AMPscript, SSJS, and HTML/CSS
• Write and optimise SQL queries in Automation Studio for segmentation, data transformation, and reporting
• Build and maintain automations, including file imports, data extracts, file transfers, and scheduled query activities
• Configure Content Builder templates and reusable content blocks
• Design complex data models and segmentation strategies in Contact Builder
• Configure and maintain Marketing Cloud Connect between Marketing Cloud and Sales or Service Cloud
• Build integrations with Salesforce and third-party systems using Marketing Cloud REST and SOAP APIs
• Ensure data integrity, data quality, subscriber management, and consent handling meet GDPR requirements
• Set up and manage deliverability, including sender authentication, IP warming, and bounce handling
• Test journeys and content across devices and email clients before release
• Analyse campaign performance and recommend improvements through A/B testing and reporting
• Troubleshoot failed sends, automations, and data issues, and provide third-line support
• Train support marketing teams to drive adoption and platform proficiency
• Create and maintain clear technical documentation
• Work closely with client marketing, CRM, and data teams to build personalised, data-driven journeys

Explore Marketing Cloud Developer at Ness Digital Engineering. Review requirements and application details.

Marketing Cloud Developer

• Design and build enterprise-grade Azure-focused cloud solutions that are highly available, secure, cost-efficient and compliant
• Own network design, security, identity and access management, including RBAC, MFA and least privilege
• Establish networking, security and identity best practices for the team
• Evolve CI/CD pipelines, infrastructure as code and cloud-resource automation
• Containerise applications and evolve architectures from monoliths toward services
• Select appropriate compute models, including App Services, serverless, VMs and Kubernetes
• Run AI services such as Azure OpenAI / AI Foundry and AI Search
• Expose, secure and govern APIs through API Management and as MCP servers
• Build robust backend APIs and contribute to frontend engineering where platform knowledge is critical
• Set up monitoring, logging and alerting
• Drive performance and cost optimisation
• Mentor colleagues and set architecture standards
• Explain complex technical topics clearly to technical and non-technical stakeholders
• Serve as a hands-on technical lead for secure, scalable and resilient Generative AI solutions, including BearingPoint's BeMind enterprise AI platform

Explore Cloud & Infrastructure Expert – Full-Stack Engineer at BearingPoint. Review requirements and application details.