GT

• Support the client’s enterprise Data Transformation Programme by helping develop and implement data strategy, governance practices and data quality initiatives. • Maintain and help coordinate the enterprise data backlog, ensuring priorities reflect agreed value opportunities and programme direction. • Support the Head of Data Strategy in establishing data governance and domain ownership model, including principles, roles and RACI. • Contribute to the Customer Data Strategy and support governance reviews, producing clear recommendations. • Coordinate foundational data activities, including data quality improvements and the move toward a sustainable Data Quality Framework. • Assist in defining and testing elements of the operating model for reporting, analytics and continuous delivery. • Prepare analysis, documentation and recommendations to support decision‑making in programme‑level forums.

• Facilitate sprint planning, daily stand-ups, backlog refinement, sprint reviews / demos, and retrospectives. • Maintain clear sprint boards, dashboards, RAID logs, dependency tracking, and delivery status reporting in Jira and DevOps / Azure DevOps. • Coach teams on Agile behaviours, including sprint goals, estimation, story clarity, acceptance criteria, Definition of Ready, and Definition of Done. • Work closely with Product Owners, Delivery Managers, Engineering Leads, Business Analysts, Test Leads, and stakeholders to keep work prioritised and ready for delivery. • Track blockers, risks, dependencies, and key decisions, ensuring they are escalated through the right delivery forums and resolved in a timely manner. • Support PI / release planning, Scrum of Scrums, ART alignment, and continuous improvement across distributed teams where required. • Improve story quality, estimation discipline, backlog hygiene, sprint predictability, and follow-through from retrospectives. • Ensure delivery reporting is clear, evidence-based, and reliable.

• Play a critical role in developing, maintaining, and scaling the pipelines and data systems that power the client's unified data platform. • Design and maintain robust, scalable ETL/ELT pipelines to ingest and process third-party and first-party datasets. • Apply transformation, normalization, and enrichment rules to ensure data consistency and usability. • Work with product managers, data architects, and content experts to align data structure with business needs. • Support the implementation of data matching and entity resolution processes using AI/ML tools and proprietary frameworks. • Build alerts, logs, and metrics to ensure data flows remain healthy and issues are identified and resolved quickly. • Build and maintain data pipelines using dbt, developing models from raw data through staging and intermediate layers up to final semantic models for use in analytics and dashboards. • Contribute to documentation, code quality standards, and internal best practices to ensure maintainability.

• The Transition Manager is responsible for planning, coordinating, and governing the end-to-end transition of data and reporting services from development teams and partners into a new managed service • Define and manage the transition plan, governance cadence, status reporting, RAID management, and phase exit readiness across contracting, mobilisation, transition, cutover, and stabilization in collaboration with our AMS partner • Coordinate stakeholders across internal teams, incumbent suppliers, incoming service providers, and platform partners to ensure timely completion of transition dependencies • Lead the end-to-end knowledge transfer process for in scope services, covering data models, platforms, technical components, and ways of working • Define the overall reporting/analytical services and capabilities model in support of the D&A strategy and operating model • Coordinate transition cutover activities, including access readiness, operational handover checkpoints, communications, and hypercare/stabilisation planning

• Define and own architecture for a new AI/Data product workstream • Design scalable backend services, data flows, and integration patterns • Guide implementation and support engineers through technical leadership • Review code, architecture decisions, and engineering standards • Collaborate with product stakeholders to translate requirements into technical solutions • Design and evolve data platform components, pipelines, and services • Contribute to AI-enabled product capabilities and agent-based workflows • Drive engineering quality, documentation, testing standards, and maintainability • Participate in hands-on implementation of complex technical initiatives

• Support Implementation Managers across customer onboarding and implementation projects. • Assist with project coordination, follow-ups, and tracking and completing implementation tasks. • Support UAT preparation and execution. • Help with testing activities and validation of customer configurations or workflows. • Prepare and update training deliverables, user guides, documentation, and support materials. • Assist with customer training preparation and, where relevant, support training sessions. • Help collect, organize, and follow up on customer questions or feedback. • Coordinate with internal teams such as Implementation, Customer Success, Product, and Support. • Support customers during onboarding and help ensure a smooth transition to product adoption. • Maintain accurate records of implementation progress, open items, and customer readiness.

Role Description We are looking for a Frontend Developer with strong Vue.js experience to help maintain and expand the YBHQ platform. The ideal candidate is comfortable working remotely in an agile environment and capable of building clean, scalable, component-driven frontend applications. Qualifications - Strong experience with Vue 3 (Composition API and script setup) - Strong knowledge of TypeScript and modern JavaScript (ES6+) - State management using Pinia - Routing with Vue Router 4 - Form handling and validation using Vee Validate and Zod - API integration experience using Axios - UI styling with Tailwind CSS and PostCSS - Experience with component libraries such as ShadCN and Reka UI - Understanding of reusable composables and utilities, especially VueUse - Experience using Git, Agile workflows, and remote collaboration Requirements - Experience with Vue i18n (nice-to-have) - Experience with Sentry logging and monitoring (nice-to-have) - Experience with Google Tag Manager and analytics/tracking integrations (nice-to-have) - Familiarity with Stripe Payment Element and subscription flows (nice-to-have) - Experience with Mux audio/video playback (nice-to-have) - Experience using TipTap, GSAP, and Swiper.js (nice-to-have) - Familiarity with NFC integrations or connected experiences (nice-to-have) - Basic understanding of frontend performance optimization and scalable component architecture (nice-to-have) Responsibilities - Build and maintain scalable Vue 3 / TypeScript frontend features - Develop reusable and high-performance UI components - Integrate external services and APIs (payments, streaming, analytics, subscriptions) - Collaborate closely with frontend, backend, and API teams in an agile environment - Contribute to frontend architecture, performance, and user experience improvements - Support the expansion of AI-enabled frontend capabilities across the platform Interview Steps - GT interview with Recruiter - Technical interview - Final interview

• Build and maintain robust backend systems • Design and implement GraphQL and REST APIs • Manage database design and optimisation using SQL, PostgreSQL, and Prisma • Develop and deploy cloud infrastructure with AWS • Implement event-driven architectures. • Integrate third-party services (Resend, Onfido, Clerk, Hubspot) • Develop software following microservices and monorepo patterns • Ensure high-quality software through automated testing and CI/CD pipelines • Collaborate effectively with engineers and non-technical team members • Troubleshoot and resolve complex technical issues

• Spend around 80% of the role providing technical guidance to client and consulting teams on AI-assisted software engineering, developer productivity, architecture, microservices, build processes, CI/CD, testing, security, and engineering workflows. • Advise and coach engineering teams on modern software engineering practices and adoption of AI tools such as Claude Code, Cursor, Codex, or GitHub Copilot. • Define technical approaches for product architecture, data flows, integrations, and build processes. • Spend around 20% of the role on hands-on architecture and delivery, including designing, developing, and documenting AI applications aligned to business outcomes. • Build or support LLM-powered applications, RAG pipelines, and AI agent systems. • Translate business requirements into technical solutions and contribute to implementation, testing, and code reviews.

• Design, train, and deploy ML models for time-series forecasting and related data tasks • Build and maintain data pipelines using cloud-native tools (AWS, GCP, or Azure) • Develop and optimize forecasting models (Prophet, ARIMA, LSTM, TimeGPT) • Collaborate with data, product, and cloud engineers to deliver reliable, scalable solutions • Participate in different stages of the project lifecycle - from discovery and PoC to production deployment, presenting your work to stakeholders