Entity: - Accenture Strategy & Consulting

Team: - Strategy & Consulting – Global Network

Practice: - Marketing Analytics

Title: - Consultant/ Manager/Analyst – Marketing & Customer Data Platforms (GCP, CDP, Agentic AI)

Job location: - Any out of 6 AI locations

About S&C - Global Network (GN) : - Accenture GN's Data & AI (AI Hub India) practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling – to outperform the competition.

WHAT'S IN IT FOR YOU

As part of our Analytics practice, you will join a worldwide network of over 20k+ smart and driven colleagues experienced in leading AI/ML/Statistical tools/Agentic AI systems, methods and applications. From data to analytics and insights to actions, our forward-thinking consultants provide analytically-informed, issue-based insights at scale to help our clients improve outcomes and achieve high performance.

What You Would Do In This Role

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 into a Customer Data Platform (CDP) by developing a strategic roadmap focused on personalized 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 operationalize 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 personalized experiences at scale.

Key Duties and Responsibilities: (GCP CDP)

Architect & 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. Containerize processing jobs with Docker for portability and scalability.
Model for Insight & Activation: Design and implement data models in BigQuery optimized for customer identity resolution, 360-degree profile creation, segmentation, and analytics.
Champion DevOps & 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 Artifact Registry, and secure credentials using Google Secret Manager.
Deploy & Serve: Develop and deploy containerized, serverless APIs (using Docker and Cloud Run) for real-time data ingestion and activation, feeding customer segments and triggers into marketing platforms.
Operationalize 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 & 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 & 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 build 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 Personalization tools like Adobe Target, Adobe Campaign, Adobe Journey Optimizer
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, structure technical solution
Prioritize CDP use cases together with the client.
Create a strategic CDP roadmap focused on data driven marketing activation.
Work with the Solution Architect to strategize, 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, datalayer implementation, Martech tools integration
Design and Implement Adobe Stack Martech tools like Adobe Target, Adobe Campaign, Adobe Journey Optimizer, 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) optimized for efficient retrieval of context for AI agents.
Design, implement, and optimize 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., personalized 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, actionable recommendations.
Project management expertise for sprint planning
Provide hands-on support and platform training for our clients.
Data processing, data engineer 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.

RTCDP (specific skills)

At least 2+ years of relevant work experience of implementing CDP solutions with deep understanding of identity resolution methods with minimum 1 year in Adobe RTCDP
At least 2+ years of relevant work experience in marketing, consulting, or analytics
At least 2+ years of experience working in an agency environment
At least 2 years of experience working as Subject matter expert in Adobe Marketing Cloud Stack
Experience with A/B testing tools like Adobe Target is a plus.
Experience with Campaign Management tools like Adobe Journey Optimizer or/and Adobe Campaign is a plus.
Experience with Adobe Marketing Cloud tools like Adobe Workfront, Adobe Experience Manager (AEM), DAM is a plus
Experience in Postman APIs is a plus
Strong hands-on with advanced JavaScript and jQuery. Able to develop custom tags/scripts using tag managers

Agentic AI (specific skills)

2+ years of hands-on experience in software engineering with a data focus, or AI/ML engineering.
At least 2 years of demonstrable experience building and managing data/AI solutions on Google Cloud Platform (GCP).
Demonstrable experience building and deploying agentic AI systems, leveraging LLMs for complex decision-making.
Hands-on experience with Retrieval Augmented Generation (RAG) pipelines and integrating external knowledge sources for LLMs.
Proven ability to apply advanced prompting techniques (e.g., Chain-of-Thought, Few-Shot) to guide and enhance LLM reasoning and output quality.
Experience working with large language models (LLMs) with a focus on their reasoning capabilities.
Hands-on experience working with Google Gemini models and their APIs/SDKs is highly preferred.
Experience with multimodal AI concepts is a significant advantage.
In-depth, hands-on expertise with core GCP data and AI services, including Vertex AI (for LLM integration, prompt engineering, RAG pipeline development).
Experience with Vertex AI RAG Engine and GCP datastore.
Advanced proficiency in Python is mandatory.
Familiarity with frameworks like Agent Development Kit (ADK) for building LLM applications and agentic workflows.
Proficient in Terraform, CI/CD practices (Cloud Build), Docker, Artifact Registry, and Google Secret Manager.
Experience in deploying and managing AI models in production environments using Vertex AI.
Experience integrating with key marketing platform APIs is highly advantageous.
Google Cloud Professional Machine Learning Engineer (PMLE) certification is highly desired.
Exceptional problem-solving and analytical capabilities, particularly in understanding and applying reasoning to complex problems.
Outstanding communication and stakeholder management skills.
A proactive, innovative, and results-driven approach.
A collaborative spirit and the capacity to mentor and guide junior team members.

Technical Skills

Direct experience building or contributing to a custom Customer Data Platform (CDP) or a similar customer-centric data system.
Deep GCP Expertise: Hands-on experience with key GCP data services: BigQuery, BigTable, Vertex AI, Dataflow, Pub/Sub, Composer (Airflow), Cloud Functions, Cloud schedular and GKE.
DevOps & Automation Mindset: Strong experience with Terraform for infrastructure provisioning and CI/CD tools (Cloud Build, Jenkins, GitLab CI).
Containerization & Serverless Deployment: Hands-on experience with Docker, managing images in Artifact Registry, and deploying applications to Cloud Run or GKE.
MLOps Experience: Familiarity with deploying and managing models using Vertex AI (or similar platforms like SageMaker/MLflow) is a strong advantage.
Modern Data Stack Knowledge: Experience with tools like dbt (Data Build Tool) for data transformation is a significant plus.
Security Best Practices: Experience using tools like Google Secret Manager or HashiCorp Vault to manage application secrets.
Marketing Domain Acumen: Understanding of core marketing concepts like identity resolution, customer segmentation, and audience activation. Experience integrating with marketing platform APIs is highly desirable. Experience with google cloud integration connector is a plus
Graph database understanding for solving advance use cases – e.g. Identity resolution
GA4/GA360, or/and Adobe Analytics, or/and Customer Journey Analytics(CJA)
Google Tag Manager, and/or Adobe Launch/AEP Web SDK, and/or Tealium iQ – any and/or any Tag Manager Tool - any one (prefer whoever has any one of these)
Adobe Journey Optimizer or/and Adobe Campaign
Google Ads, DV360, Campaign Manager, Facebook Ads Manager, The Trading desk etc.
Deep Cloud experience (GCP, AWS, Azure)
Advance level Python, SQL, Shell Scripting experience
Advance level JavaScript /jQuery
Data Migration, DevOps, MLOps, Terraform Script programmer
Basic HTML
Adobe RTCDP (AEP) developer and any other CDP platforms experience e.g., Lytics CDP platform developer, or/and Segment CDP platform developer, or/and Tealium CDP platform developer, or/and Salesforce CDP platform developer, or/and Custom CDP developer on any cloud
Adobe Target and/or Optimizely or any personalization or A/B testing tool
Adobe Marketing Cloud - Adobe Workfront, Adobe Experience Manager (AEM), DAM
Experience on debuggers like Adobe Launch debugger, Omnibug, Charles, Browser stack, etc.
Experience working and designing Agentic AI systems for complex reasoning and multi-step task.
Advance prompt engineering (e.g., Chain-of-Thought, ReAct) to optimize LLM reasoning.
Experience on using Agent Development Kit(Adk)
Experience working with Multimodal LLM's. Preferably Gemini.
Experience working on Vertex AI Rag engine and GCP datastores.
Experience using GCP Evaluation and Grounding SDK.

Soft Skills

Strong problem solving skills
Good team player
Attention to details
Good communication skills

Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.

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