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Accenture

Advises businesses and runs their technology

Google Data & AI Engineer Lead

Data EngineeringConfirmed live in the last 24 hours
Full-timeRemote in IndiaNo salary listed

About the Job

Requirements

  • Hands-on experience delivering Google Cloud data and AI products across design, build, and production operations, with deep expertise in Google’s data and AI product portfolio.
  • Strong programming experience in Python and SQL.
  • Depth in Google Cloud data engineering, including BigQuery performance and cost optimization, Dataflow, Pub/Sub, Dataproc, Cloud Composer or Dataform, and Cloud Storage or BigLake.
  • Applied machine learning and generative AI experience on Google Cloud, including Vertex AI Pipelines, Model Registry and Endpoints, BigQuery ML, Gemini models, Retrieval-Augmented Generation, and Vector Search.
  • Engineering fundamentals including Infrastructure as Code with Terraform, continuous integration and continuous delivery, DataOps or MLOps, observability, and security fundamentals such as IAM, CMEK, DLP, and Dataplex.
  • Domain depth in one or more of Customer 360 and Marketing Intelligence, Data Platform Modernization, Analytics and Business Intelligence using Looker, or Generative and Agentic AI.
  • Ability to contribute to reusable assets, points of view, accelerators, and estimates.

Responsibilities

  • Design, build, test, and deploy complex data pipelines, analytics, and machine learning or generative AI solutions on Google Cloud across the delivery lifecycle, from requirements gathering through production support.
  • Work directly with clients to understand business and data challenges, translate requirements into technical designs, and serve as a technical advisor throughout projects.
  • Lead and mentor onshore and offshore engineers, conduct design and code reviews, and collaborate with cross-functional stakeholders to support alignment and delivery.
  • Apply DataOps and MLOps practices and Infrastructure as Code using Terraform within an Agile framework.
  • Build accelerators, reference architectures, and points of view to make Google Cloud Data and AI delivery repeatable and tied to measurable outcomes.
  • Build and migrate data warehouses and lakehouses to BigQuery using Dataflow, Dataproc, Datastream, and Cloud Composer.
  • Deliver governed analytics using Looker and LookML with BigQuery.
  • Contribute to designing and developing generative and agentic AI solutions using Vertex AI, Gemini models, and Retrieval-Augmented Generation.
  • Build, deploy, and monitor machine learning models using Vertex AI Pipelines, Model Registry, and BigQuery ML.
  • Unify customer data in Google Cloud and use BigQuery and Vertex AI for predictive segments and personalization.
  • Build event-driven real-time and streaming analytics pipelines using Pub/Sub, Dataflow, and BigQuery.
  • Implement data cataloging, lineage, quality, and access controls using Dataplex, DLP, and IAM.

Desired Qualifications

  • Java or Scala experience with Apache Beam.
  • Google Cloud Professional Data Engineer or Professional Machine Learning Engineer certification.
  • Experience with Looker and LookML, Dataplex governance, and agent frameworks such as Vertex AI Agent Builder or Agent Development Kit.
  • Experience mentoring engineers in an onshore and offshore Agile delivery model.

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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