CDP Consultant

A Consultant/Manager/Analyst for Customer Data Platforms serves as the day-to-day marketing technology point of contact and helps our clients get value out of their investment in a Customer Data Platform (CDP) by developing a strategic roadmap focused on personalised activation. You will be working with a multidisciplinary team of Solution Architects, Data Engineers, Data Scientists, and Digital Marketers.
As part of that, we are seeking a highly skilled Consultant/Manager/Analyst to architect, build, and operationalise custom Customer Data Platforms (CDPs), Agentic AI systems and marketing data solutions on the Google Cloud Platform (GCP). You will be at the intersection of data engineering, MLOps, and marketing technology, building the foundational infrastructure that enables our clients to understand their customers, predict their needs, and deliver personalised experiences at scale.
Responsibilities:
Architect and Design: Lead the technical design and architecture of enterprise-grade, custom CDPs and marketing data warehouses on Google Cloud Platform (GCP).
Build Production-Grade Data Pipelines: Engineer robust, scalable, and automated data pipelines for both streaming and batch ingestion using services like Cloud Dataflow, Pub/Sub, and Cloud Functions. Containerise processing jobs with Docker for portability and scalability.
Model for Insight and Activation: Design and implement data models in BigQuery optimised for customer identity resolution, 360-degree profile creation, segmentation, and analytics.
Champion DevOps and MLOps: Champion and implement Infrastructure as Code (IaC) using Terraform. Build CI/CD pipelines using Cloud Build to automate testing and deployment, manage container images in Artefact Registry, and secure credentials using Google Secret Manager.
Deploy and Serve: Develop and deploy containerised, serverless APIs (using Docker and Cloud Run) for real-time data ingestion and activation, feeding customer segments and triggers into marketing platforms.
Operationalise Machine Learning: Collaborate with data scientists to productionize ML models (e. g., propensity, LTV, segmentation) using the Vertex AI platform. Build automated training pipelines and deploy models for real-time inference.
Collaborate and Innovate: Work within a multi-disciplinary team to translate business requirements into technical solutions, prototype new approaches, and provide expert guidance on the art of the possible with GCP and modern data engineering.
Ensure Governance and Security: Implement solutions that adhere to data governance best practices and privacy regulations (e. g., GDPR, CCPA), ensuring data is handled securely and ethically.
Key Duties and Responsibilities: (RTCDP):
Be a platform expert in Adobe RTCDP (Adobe Real-Time CDP). Developer-level expertise on Adobe RTCDP (Adobe Experience Platform) is a must, with other CDP platforms like Lytics, Segment, Amperity, Tealium, Treasure Data, etc., including custom-built CDPs as an added advantage.
Deep developer-level expertise for real-time event tracking for web analytics, e. g., Google Tag Manager, Adobe Launch, Adobe Web SDK, etc.
Provide deep domain expertise in our client's business and broad knowledge of digital marketing together with a Marketing Strategist industry
Deep expert-level knowledge of reporting tools like GA360/GA4 Adobe Analytics, Customer Journey Analytics
Deep expert-level knowledge of paid media destinations - Google Ads, DV360 Campaign Manager, Facebook Ads Manager, The Trading Desk, etc.
Deep developer expertise for Journey Orchestration and Personalisation tools like Adobe Target, Adobe Campaign, Adobe Journey Optimiser.
Assess and audit the current state of a client's marketing technology stack (MarTech), including data infrastructure, ad platforms and data security policies, together with a solutions architect.
Conduct stakeholder interviews and gather business requirements
Translate business requirements into BRDs, CDP customer analytics use cases, and structure technical solution
Prioritise CDP use cases together with the client.
Create a strategic CDP roadmap focused on data-driven marketing activation.
Work with the Solution Architect to strategise, architect, and document a scalable CDP/Martech implementation, tailored to the client's needs.
Able to integrate multiple Martech tools.
Ensure analytics are consistently implemented across digital properties.
Diagnose and troubleshoot analytics/Martech implementation and platform configuration issues.
Perform end-to-end QA testing for integrations.
Coordinate with website developers for Analytics integration, data layer implementation, Martech tools integration.
Design and implement Adobe Stack Martech tools like Adobe Target, Adobe Campaign, Adobe Journey Optimiser, Adobe Launch, Adobe Web SDK, Adobe Analytics, Customer Journey Analytics.
Deep domain expertise in Tag Management, Journey Orchestration, Campaign Management, A/B Testing.
Perform technical analysis & design for Martech related initiatives.
Define requirements for Martech implementation/reporting dashboard.
Key Duties and Responsibilities: (Agentic AI)
Architect the core interaction logic and decision-making frameworks for enterprise-grade, agentic AI systems within marketing on GCP.
Leverage Google Agent Development Kit (ADKs) and APIs to orchestrate complex, multi-step agentic workflows, focusing on reasoning capabilities.
Design agentic AI systems for scalability, robustness, and real-time responsiveness in autonomous marketing decision-making.
Design and implement data storage strategies (Datastores) optimised for efficient retrieval of context for AI agents.
Design, implement, and optimise Retrieval Augmented Generation (RAG) pipelines to equip Gemini agents with contextually relevant information from various knowledge sources.
Leverage Gemini models' reasoning capabilities to enable agents for complex analysis, strategic planning, and problem-solving in marketing contexts.
Develop and apply advanced prompting techniques (e. g., Chain-of-Thought, Few-Shot) to guide and enhance the reasoning, accuracy, and output quality of AI agents.
Implement and leverage grounding & evaluation capabilities within Agentic AI systems to ensure outputs are factually accurate, contextually relevant, and traceable to specific data sources for marketing applications.
Develop and deploy AI-driven solutions for generating multimodal marketing assets (e. g., personalised images, video snippets, audio messages) powered by Gemini.
Implement LLMops best practices for the lifecycle management of agentic AI models, including CI/CD for AI components.
Ensure secure and compliant interactions for AI agents, managing credentials and secrets relevant to AI model access.
Implement robust monitoring, logging, and observability specifically for the performance, decision paths, and output quality of agentic AI systems.
Prototype new approaches and provide expert guidance on GCP AI services, Gemini, RAG, advanced prompting, and reasoning AI techniques.
Create insights presentations and client-ready decks, effectively communicating findings and recommendations.
Mentor and guide junior resources, fostering a collaborative and growth-oriented team environment.
Demonstrate strong communication skills, both verbal and written, to effectively convey complex concepts and insights to stakeholders.
Develop strong relationships with clients at all levels, understanding their specific challenges and opportunities.
Other roles and responsibilities:
Business intelligence expertise for insights and actionable recommendations.
Project management expertise for sprint planning.
Provide hands-on support and platform training for our clients.
Data processing, data engineering, and data schema/models expertise for CDPs to work on data models, unification logic, etc.
Work with Business Analysts, Data Architects, Technical Architects, DBAs to achieve project objectives - delivery dates, quality objectives, etc.

Experience
5-9 yrs