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Accenture

Advises businesses and runs their technology

Insights & Platforms Senior Manager - Multiple Teams

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

About the Job

Requirements

  • A B.Tech or M.Tech from a reputed engineering college is required.
  • A Master's or M.Tech degree in Computer Science is required.
  • A Master's degree in Statistics, Econometrics, or Economics from a reputed institute is required.
  • An M.Phil or Ph.D in Statistics, Econometrics, or a related field is required.
  • At least 10 years of hands-on experience in data engineering or software engineering with a data focus is required.
  • At least 8 years of demonstrable experience building and managing data solutions on a major cloud platform is required; Google Cloud Platform is strongly preferred, and AWS or Azure experience is valuable.
  • At least 8 years of relevant work experience in marketing, consulting, or analytics is required.
  • A strong understanding of data governance and compliance, including personally identifiable information, protected health information, GDPR, and CCPA, is required.
  • Strong experience in ETL, data aggregation, and transformation using SQL is required.
  • For the RTCDP specialization, at least 4 years of relevant experience implementing CDP solutions, including at least 1 year with Adobe RTCDP, is required.
  • For the RTCDP specialization, at least 4 years of relevant work experience in marketing, consulting, or analytics and at least 5 years of experience in an agency environment are required.
  • For the RTCDP specialization, at least 5 years of experience as a subject-matter expert in Adobe Marketing Cloud is required.
  • For the Agentic AI specialization, at least 5 years of hands-on experience in software engineering with a data focus or AI/ML engineering is required.
  • For the Agentic AI specialization, at least 3 years of demonstrable experience building and managing data or AI solutions on Google Cloud Platform is required.
  • For the Agentic AI specialization, advanced proficiency in Python is mandatory.
  • The posting identifies developer-level expertise in Adobe RTCDP / Adobe Experience Platform and real-time event tracking as requirements for the RTCDP work.
  • The posting identifies hands-on advanced JavaScript and jQuery experience, including developing custom tags or scripts using tag managers, for RTCDP work.
  • The posting identifies demonstrable experience building and deploying agentic AI systems using large language models for complex decision-making, hands-on Retrieval Augmented Generation pipelines, and applying advanced prompting techniques as requirements for Agentic AI work.
  • The posting requires hands-on experience with Google Gemini models and their APIs or SDKs as highly preferred, and familiarity with the Agent Development Kit for building LLM applications and agentic workflows.
  • The posting requires proficiency in Terraform, CI/CD practices, Docker, Artifact Registry, and Google Secret Manager for Agentic AI work.
  • The posting requires experience with source control systems such as Git or Bitbucket and continuous-integration tools such as Jenkins.
  • The posting requires experience in requirements gathering, solution design, tag implementation and audits, and MarTech integration.
  • The posting requires experience defining website or app measurement frameworks, recommending KPIs, and driving customer-engagement strategy.
  • The posting requires the ability to manage large volumes of structured and unstructured data and extract and clean data for analysis.
  • The posting requires familiarity with the relevant technical skills specified for the chosen specialization, including cloud data platforms, CDP and marketing technology tools, analytics, data engineering, and AI/ML systems.

Responsibilities

  • Lead technical design and architecture of enterprise-grade custom Customer Data Platforms and marketing data warehouses on Google Cloud Platform.
  • Engineer 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 profiles, segmentation, and analytics.
  • Implement infrastructure as code using Terraform; build CI/CD pipelines with Cloud Build; manage 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, connecting 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 on Vertex AI.
  • Translate business requirements into technical solutions, prototype approaches, and advise on GCP and modern data engineering capabilities.
  • Implement data governance and security practices that comply with privacy regulations such as GDPR and CCPA.
  • Serve as a platform expert in Adobe RTCDP and work with other CDP platforms, including Lytics, Segment, Amperity, Tealium, and Treasure Data, as well as custom-built CDPs.
  • Implement real-time web analytics event tracking using tools such as Google Tag Manager, Adobe Launch, and Adobe Web SDK.
  • Assess and audit clients’ MarTech stacks, including data infrastructure, advertising platforms, and data-security policies, with a solutions architect.
  • Conduct stakeholder interviews, gather business requirements, document business requirement documents and CDP customer analytics use cases, and structure technical solutions.
  • Prioritize CDP use cases with clients and create strategic CDP roadmaps focused on data-driven marketing activation.
  • Work with solution architects to strategize, architect, and document scalable CDP and MarTech implementations tailored to client needs, integrating multiple MarTech tools.
  • Ensure consistent analytics implementation across digital properties; diagnose and troubleshoot analytics and MarTech implementations and platform configurations; and perform end-to-end integration quality assurance.
  • Coordinate with website developers on analytics integration, data-layer implementation, and MarTech-tool integration.
  • Design and implement Adobe MarTech tools, including Adobe Target, Adobe Campaign, Adobe Journey Optimizer, Adobe Launch, Adobe Web SDK, Adobe Analytics, and Customer Journey Analytics.
  • Perform technical analysis and design for MarTech initiatives and define requirements for MarTech implementations and reporting dashboards.
  • Architect interaction logic and decision-making frameworks for enterprise agentic AI systems for marketing on GCP.
  • Use Google Agent Development Kit and APIs to orchestrate multi-step agentic workflows with reasoning capabilities.
  • Design agentic AI systems for scalability, robustness, and real-time responsiveness in autonomous marketing decisions.
  • Design data-storage strategies and datastores for efficient retrieval of context by AI agents.
  • Design and optimize Retrieval Augmented Generation pipelines that supply Gemini agents with relevant context from knowledge sources.
  • Use Gemini reasoning capabilities for complex analysis, strategic planning, and problem-solving in marketing contexts.
  • Apply prompting techniques such as Chain-of-Thought and Few-Shot to improve agent reasoning, accuracy, and output quality.
  • Implement grounding and evaluation capabilities so 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.
  • Implement LLMOps lifecycle practices for agentic AI models, including CI/CD for AI components.
  • Secure and govern AI-agent interactions, including management of credentials and secrets for model access.
  • Implement monitoring, logging, and observability for agentic AI performance, decision paths, and output quality.
  • Create client-ready insights presentations and decks communicating findings and recommendations.
  • Mentor and guide junior resources and build client relationships at all levels to understand client challenges and opportunities.
  • Provide business intelligence expertise to generate insights and actionable recommendations.
  • Manage project activities, including sprint planning, and provide hands-on client support and platform training.
  • Apply data processing, data engineering, and data schema and modeling expertise to CDP models and unification logic.
  • Work with business analysts, data architects, technical architects, and database administrators to meet project delivery dates and quality objectives.

Desired Qualifications

  • Experience with Google Analytics, Adobe Analytics, or Adobe Customer Journey Analytics is a plus.
  • Certification in Adobe Launch, Adobe Experience Platform Web SDK, Google Tag Manager, or Tealium iQ is a plus.
  • Experience with mobile analytics implementations is desirable.
  • Programming experience in PySpark, Python, or shell scripts is desirable outside the Agentic AI specialization, where advanced Python is mandatory.
  • Experience with RDBMS, T-SQL, or NoSQL is a plus.
  • Experience deploying and operationalizing code is an advantage.
  • Experience with A/B testing tools such as Adobe Target is a plus.
  • Experience with campaign-management tools such as Adobe Journey Optimizer or Adobe Campaign is a plus.
  • Experience with Adobe Workfront, Adobe Experience Manager, or digital asset management tools is a plus.
  • Hands-on experience with Gemini models and their APIs or SDKs is highly preferred.
  • Experience with multimodal AI concepts is a significant advantage.
  • Experience with Vertex AI RAG Engine and GCP datastore is desired.
  • Google Cloud Professional Machine Learning Engineer certification is highly desired.
  • Experience integrating key marketing-platform APIs is highly advantageous.
  • Experience with dbt for data transformation is a significant plus.
  • Experience with Vertex AI or similar platforms such as SageMaker or MLflow for deploying and managing models is an advantage.
  • Experience with Google Secret Manager or HashiCorp Vault for secrets management is desired.
  • Understanding of graph databases for identity-resolution use cases is desired.
  • Experience with Adobe RTCDP and other CDP platforms, including Lytics, Segment, Tealium, Salesforce CDP, or custom CDPs, is desired.
  • Experience with Adobe Target, Optimizely, or other personalization and A/B testing tools is desired.
  • Experience with Adobe Marketing Cloud tools such as Adobe Workfront, Adobe Experience Manager, and digital asset management is desired.
  • Experience with debugging tools such as Adobe Launch Debugger, Omnibug, Charles, or BrowserStack is desired.
  • Experience designing agentic AI systems for complex reasoning and multi-step tasks is desired.
  • Experience with advanced prompt engineering techniques such as Chain-of-Thought or ReAct is desired.
  • Experience using the Agent Development Kit is desired.
  • Experience with multimodal large language models, preferably Gemini, is desired.
  • Experience with GCP Evaluation and Grounding SDK is desired.

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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