Reads like a Data Engineer role: pipelines and data infrastructure.
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Design, build, test and deploy data pipelines and ML/GenAI solutions on Google Cloud
Translate client requirements into technical designs and advise the client
Lead and mentor on-shore and off-shore engineers, running design and code reviews
Apply DataOps/MLOps and Terraform within an Agile delivery framework
Build accelerators, reference architectures and POVs for repeatable Google Data & AI delivery
Design, build, test, and deploy complex data pipelines, analytics, and ML/GenAI solutions on Google Cloud
translate requirements into technical designs, and act as a technical advisor for the client throughout the project
Lead and mentor on-shore and off-shore engineers, conduct design and code reviews
Apply DataOps/MLOps practices and Infrastructure as Code (Terraform) within an Agile framework
Build accelerators, reference architectures, and POVs that make Google Data & AI delivery repeatable
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.
In the employer’s words · Read in context
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
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Early. Similar jobs usually come down between day 6 and day 54.
At Accenture, jobs usually come down by about day 1.
From 11,508 similar postings that came down, and 2,618 of Accenture’s. Coming down is not always a hire.
423 open jobs
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Job Title - AGBG Google Data & AI Engineer – Specialist (Lead) Management Level: 09-Specialist Location: All over India Must have skills Hands-on Google Cloud (GCP) Data & AI product delivery (design/build/run in production) with deep expertise in the Google data and AI product portfolio. Strong programming experience in Python and SQL; Java/Scala with Apache Beam is an advantage. GCP data engineering depth: BigQuery (performance and cost optimization), Dataflow, Pub/Sub, Dataproc, Cloud Composer/Dataform, Cloud Storage/BigLake. Applied ML and Generative AI on GCP: Vertex AI (Pipelines, Model Registry, Endpoints), BigQuery ML, Gemini models, RAG, and Vector Search. Engineering fundamentals: Infrastructure as Code (Terraform), CI/CD, DataOps/MLOps, observability, and security basics (IAM, CMEK, DLP, Dataplex). Domain depth in one or more: Customer 360 & Marketing Intelligence, Data Platform Modernization, Analytics & BI (Looker), Generative & Agentic AI. Offering mindset: ability to contribute to reusable assets, POVs, accelerators, and estimates. Good to have Google Cloud Professional Data Engineer or Professional Machine Learning Engineer certification. Experience with Looker (LookML), Dataplex governance, and agent frameworks (Vertex AI Agent Builder/Agent Development Kit). Experience mentoring engineers in an on-shore/off-shore Agile delivery model. Job Summary L9 Specialist who leads client-facing delivery of data, analytics, and AI solutions on Google Cloud, with deep GCP product expertise and domain depth in one or more of Data Platform Modernization, Analytics & BI, Generative & Agentic AI, or Customer 360. Drives end-to-end engineering (build-to-run), mentors teams, and shapes repeatable offerings (POVs, accelerators, reference architectures) tied to measurable outcomes. Roles & Responsibilities Hands-On Data & AI Engineering: Design, build, test, and deploy complex data pipelines, analytics, and ML/GenAI solutions on Google Cloud, working across the entire delivery lifecycle from requirements gathering to production support. Client-Facing Solutioning: Work directly with clients to understand business and data challenges, translate requirements into technical designs, and act as a technical advisor for the client throughout the project. Team Leadership & Collaboration: Lead and mentor on-shore and off-shore engineers, conduct design and code reviews, and collaborate with cross-functional stakeholders to ensure alignment and delivery excellence. Modern Engineering & Agile Delivery: Apply DataOps/MLOps practices and Infrastructure as Code (Terraform) within an Agile framework to deliver high-quality solutions at pace. Reusable Assets & Offerings: Build accelerators, reference architectures, and POVs that make Google Data & AI delivery repeatable and tied to measurable outcomes. Leverage your expertise to deliver outstanding results in one or more of the following Google Cloud Data & AI domains: – Data Platform & Modernization: Build and migrate data warehouses and lakehouses to BigQuery using Dataflow, Dataproc, Datastream, and Cloud Composer. – Analytics & Business Intelligence: Deliver governed analytics using Looker (LookML) and BigQuery. – Generative & Agentic AI: Contribute to the design and development of AI solutions using Vertex AI, Gemini models, and Retrieval-Augmented Generation (RAG). – Applied ML & MLOps: Build, deploy, and monitor ML models using Vertex AI Pipelines, Model Registry, and BigQuery ML. – Customer 360 & Marketing Intelligence: Unify customer data in GCP; use BigQuery and Vertex AI for predictive segments and personalization. – Real-Time & Streaming Analytics: Build event-driven pipelines with Pub/Sub, Dataflow, and BigQuery. – Data Governance & Security: Implement cataloging, lineage, quality, and access controls with Dataplex, DLP, and IAM. About Our Company | Accenture About Accenture
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Yes. We’ve followed 3 other AGBG Google Data & AI Engineer - Specialist (Lead) jobs there since November 2026. All 3 are still up.
Large employers often post one title for several teams, so these can be separate openings.
New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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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