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Accenture

Advises businesses and runs their technology

Customer Data Platform Consultant - Multiple Teams

Data EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • A B.Tech or M.Tech in engineering, a master's or M.Tech in Computer Science, a master's degree in Statistics, Econometrics, or Economics, or an M.Phil or Ph.D. in Statistics, Econometrics, or a related field.
  • At least 6 years of hands-on experience in data engineering or software engineering with a data focus.
  • At least 2 years of demonstrable experience building and managing data solutions on a major cloud platform; Google Cloud Platform is strongly preferred, while AWS or Azure experience is valuable.
  • At least 2 years of relevant work experience in marketing, consulting, or analytics.
  • Strong understanding of data governance and compliance, including personally identifiable information, protected health information, GDPR, and CCPA.
  • Experience gathering requirements, designing solutions, implementing tags, conducting audits, and integrating marketing technology tools.
  • Strong experience in ETL, data aggregation, and transformation using SQL.
  • At least 2 years of experience implementing customer data platform solutions and understanding identity resolution methods, including at least 1 year in Adobe RTCDP.
  • At least 2 years of experience working in an agency environment and at least 2 years as a subject matter expert in the Adobe Marketing Cloud stack.
  • Strong hands-on experience with advanced JavaScript and jQuery, including developing custom tags and scripts using tag managers.
  • At least 2 years of hands-on experience in software engineering with a data focus or AI/ML engineering, and at least 2 years building and managing data or AI solutions on Google Cloud Platform.
  • Demonstrable experience building and deploying agentic AI systems using large language models for complex decision-making, and hands-on experience with Retrieval Augmented Generation pipelines and external knowledge sources.
  • Experience applying advanced prompting techniques, working with large language models focused on reasoning, and using multimodal AI concepts.
  • Hands-on expertise with core Google Cloud Platform data and AI services, including Vertex AI, Vertex AI RAG Engine, and Google Cloud datastores; advanced proficiency in Python is mandatory.
  • Familiarity with the Agent Development Kit for building large language model applications and agentic workflows.
  • Proficiency in Terraform, continuous integration and continuous deployment practices using Cloud Build, Docker, Artifact Registry, and Google Secret Manager.
  • Experience deploying and managing AI models in production using Vertex AI.
  • Strong understanding of data services and tools including BigQuery, BigTable, Dataflow, Pub/Sub, Composer (Airflow), Cloud Functions, Cloud Scheduler, and GKE.
  • Strong experience with Terraform for infrastructure provisioning and continuous integration and continuous deployment tools such as Cloud Build, Jenkins, and GitLab CI.
  • Hands-on experience with Docker, managing images in Artifact Registry, and deploying applications to Cloud Run or GKE.
  • Experience using Google Secret Manager or HashiCorp Vault to manage application secrets.
  • Understanding of customer identity resolution, customer segmentation, and audience activation; experience integrating marketing platform APIs is advantageous.
  • Understanding of graph databases for identity-resolution use cases.
  • Advanced JavaScript and jQuery, basic HTML, and experience with SQL and shell scripting.
  • Proficiency in Microsoft Excel, Word, and PowerPoint.
  • Strong problem-solving skills, attention to detail, and communication skills.

Responsibilities

  • Architect and design enterprise-grade custom customer data platforms and marketing data warehouses on Google Cloud Platform.
  • Build robust, scalable, automated streaming and batch data pipelines using Cloud Dataflow, Pub/Sub, and Cloud Functions, and containerize processing jobs with Docker.
  • Design and implement BigQuery data models for customer identity resolution, 360-degree customer profiles, segmentation, and analytics.
  • Implement infrastructure as code using Terraform; build continuous integration and continuous deployment pipelines with Cloud Build; manage container images in Artifact Registry; and secure credentials with Google Secret Manager.
  • Develop and deploy containerized serverless APIs using Docker and Cloud Run for real-time data ingestion and activation, delivering customer segments and triggers to marketing platforms.
  • Collaborate with data scientists to productionize machine-learning models, build automated training pipelines, and deploy models for real-time inference using Vertex AI.
  • Translate business requirements into technical solutions, prototype approaches, and provide guidance on Google Cloud Platform and modern data engineering.
  • Implement data governance and security practices and comply with privacy regulations, including GDPR and CCPA.
  • Serve as a platform expert in Adobe RTCDP and provide developer-level expertise on Adobe Experience Platform and other customer data platforms.
  • Assess and audit clients’ marketing technology stacks, including data infrastructure, advertising platforms, and data-security policies, with a solutions architect.
  • Conduct stakeholder interviews, gather requirements, translate them into business requirements documents and customer-data-platform analytics use cases, and structure technical solutions.
  • Prioritize customer-data-platform use cases with clients and create strategic roadmaps focused on data-driven marketing activation.
  • Work with solution architects to strategize, architect, and document scalable customer-data-platform and marketing-technology implementations tailored to client needs, integrating multiple marketing technology tools.
  • Ensure consistent analytics implementation across digital properties; diagnose and troubleshoot analytics and marketing-technology implementation and configuration issues; and perform end-to-end integration quality assurance testing.
  • Coordinate with website developers on analytics integration, data-layer implementation, and marketing-technology integrations.
  • Design and implement Adobe marketing technology tools, including Adobe Target, Adobe Campaign, Adobe Journey Optimizer, Adobe Launch, Adobe Web SDK, Adobe Analytics, and Customer Journey Analytics.
  • Conduct technical analysis and design for marketing-technology initiatives and define requirements for implementation and reporting dashboards.
  • Architect interaction logic and decision-making frameworks for enterprise agentic AI systems in marketing on Google Cloud Platform.
  • Use Google Agent Development Kit and APIs to orchestrate multi-step agentic workflows with reasoning capabilities, designing systems for scalability, robustness, and real-time response.
  • Design data-storage strategies and Retrieval Augmented Generation pipelines that provide AI agents with relevant context from knowledge sources.
  • Use Gemini models to enable complex analysis, strategic planning, and problem-solving in marketing contexts; apply prompting techniques such as Chain-of-Thought and Few-Shot prompting.
  • Implement grounding and evaluation capabilities to ensure agentic AI outputs are accurate, relevant, and traceable to data sources.
  • Develop and deploy Gemini-powered AI solutions that generate personalized multimodal marketing assets, including images, video snippets, and audio messages.
  • Apply LLMOps practices to manage agentic AI model lifecycles, including continuous integration and deployment for AI components; secure credentials and secrets for AI model access.
  • Monitor, log, and provide observability for agentic AI system performance, decision paths, and output quality.
  • Create client-ready insight presentations and communicate findings and recommendations to stakeholders.
  • Build strong client relationships and understand clients’ challenges and opportunities.
  • Provide business intelligence insights and actionable recommendations; support sprint planning and project management.
  • Provide hands-on platform support and training to clients.
  • Work on customer-data-platform data processing, data engineering, schemas, and models, including data models and unification logic.
  • Coordinate with business analysts, data architects, technical architects, and database administrators to meet project delivery dates and quality objectives.
  • Mentor and guide junior resources.

Desired Qualifications

  • Experience with Google Analytics, Adobe Analytics, or Adobe Customer Journey Analytics.
  • Developer experience with Adobe Launch, Adobe Experience Platform Web SDK, Google Tag Manager, or Tealium iQ; certification in any one is a plus.
  • Experience implementing consent-management platforms such as Sourcepoint or OneTrust on digital properties.
  • Experience defining website or application measurement frameworks, recommending key performance indicators, and developing customer-engagement strategy.
  • Experience with mobile analytics implementations.
  • Programming experience in PySpark, Python, or shell scripts; relational databases, T-SQL, or NoSQL.
  • Experience deploying and operationalizing code; experience with Git, Bitbucket, or Jenkins for source control, builds, and continuous integration.
  • Experience with Adobe Target or other A/B testing tools; Adobe Journey Optimizer or Adobe Campaign; Adobe Workfront, Adobe Experience Manager, or digital asset management tools; and Postman APIs.
  • Experience integrating with marketing platform APIs.
  • Google Cloud Professional Machine Learning Engineer certification is highly desired.
  • Experience deploying and managing machine-learning models using Vertex AI or platforms such as SageMaker or MLflow.
  • Experience using dbt for data transformation.
  • Experience with Google Cloud integration connectors.
  • Experience with GA4/GA360, Adobe Analytics, or Customer Journey Analytics; Google Tag Manager, Adobe Launch/Adobe Experience Platform Web SDK, or Tealium iQ; Adobe Journey Optimizer or Adobe Campaign; Google Ads, DV360, Campaign Manager, Facebook Ads Manager, or The Trade Desk.
  • Experience with cloud platforms including Google Cloud Platform, AWS, or Azure; data migration; DevOps, MLOps, or Terraform scripting.
  • Experience with customer data platforms including Adobe RTCDP, Lytics, Segment, Tealium, Salesforce CDP, or custom-built platforms.
  • Experience with Adobe Target, Optimizely, or other personalization and A/B testing tools; Adobe Workfront, Adobe Experience Manager, and digital asset management tools.
  • Experience with debugging tools such as Adobe Launch debugger, Omnibug, Charles, or BrowserStack.
  • Experience designing agentic AI systems for complex reasoning and multi-step tasks; advanced prompting such as Chain-of-Thought or ReAct; Agent Development Kit; multimodal large language models, preferably Gemini; Vertex AI RAG Engine and Google Cloud datastores; and Google Cloud evaluation and grounding SDKs.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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