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Architect and design custom CDPs and marketing data warehouses on GCP
Build streaming and batch data pipelines with Dataflow, Pub/Sub, and Cloud Functions
Deploy serverless APIs on Cloud Run for real-time data ingestion and activation
Productionize ML models such as propensity and LTV on Vertex AI
Create a strategic CDP roadmap focused on data-driven marketing activation
Lead the technical design and architecture of enterprise-grade, custom CDPs and marketing data warehouses on Google Cloud Platform (GCP)
Engineer robust, scalable, and automated data pipelines for both streaming and batch ingestion using services like Cloud Dataflow, Pub/Sub, and Cloud Functions
Develop and deploy containerized, serverless APIs (using Docker and Cloud Run) for real-time data ingestion and activation
Collaborate with data scientists to productionize ML models (e.g., propensity, LTV, segmentation) using the Vertex AI platform
Create a strategic CDP roadmap focused on data driven marketing activation
Experience on debuggers like Adobe Launch debugger, Omnibug, Charles, Browser stack, etc.
Good communication skills
Experience working and designing Agentic AI systems for complex reasoning and multi-step task.
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.
· 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
- Masters/M Tech in Computer Science - Master degree in Statistics/Econometrics/ Economics from reputed institute - M.Phil/Ph.D in Statistics/Econometrics or related field
- Master degree in Statistics/Econometrics/ Economics from reputed institute - M.Phil/Ph.D in Statistics/Econometrics or related field - 8+ years of hands-on experience in data engineering or software engineering with a data focus.
- 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)
- Advance level Python, SQL, Shell Scripting experience - Advance level JavaScript /jQuery - Data Migration, DevOps, MLOps, Terraform Script programmer
- Experience in mobile analytics implementations is a nice to have - Good to have programming experience in PySpark, Python, Shell Scripts. - RDBMS, TSQL, NoSQL experience is a plus
- 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.
- Deep Cloud experience (GCP, AWS, Azure) - Advance level Python, SQL, Shell Scripting experience - Advance level JavaScript /jQuery
- Experience in defining measurement frameworks for websites/app, suggesting KPIs to track, driving strategy for customer engagement - Strong experience in ETL, data aggregation and transformation using SQL is a must - Experience in mobile analytics implementations is a nice to have
- 8+ years of hands-on experience in data engineering or software engineering with a data focus. - At least 6+ years of demonstrable experience building and managing data solutions on a major cloud platform (GCP is strongly preferred; AWS/Azure experience is valuable) - At least 4+ years of relevant work experience in marketing, consulting, or analytics
- 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
- 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.
· 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).
· 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.
- 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.
- 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.
· 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.
- Experience with source control systems such as Git, Bitbucket, and Jenkins build and continuous integration tools. - Proficient in Excel, MS word, PowerPoint, etc RTCDP (specific skills)
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)
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.
- 5+ years of hands-on experience in software engineering with a data focus, or AI/ML engineering. - At least 3 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.
- 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.
- 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.
- 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.
· 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
- 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.
· 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.
- Good to have programming experience in PySpark, Python, Shell Scripts. - RDBMS, TSQL, NoSQL experience is a plus - Manage large volumes of structured and unstructured data, extract & clean data to make it amenable for analysis.
- 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.
· 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.
- Advance level JavaScript /jQuery - Data Migration, DevOps, MLOps, Terraform Script programmer - Basic HTML
- 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
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale.
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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
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Yes. We’ve followed 2 other I&P - GN - SONG - AI & Data - Marketing - CDP - Manager jobs there since November 2026. All 2 are still up.
We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
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)
Key Duties and Responsibilities: (RTCDP)
Key Duties and Responsibilities: (Agentic AI)
Other roles and responsibilities
Who are we looking for?
RTCDP (specific skills)
Agentic AI (specific skills)
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
Soft Skills:
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
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