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, analytics and ML/GenAI solutions on Google Cloud
Translate client requirements into target-state data and AI architectures
Manage and mentor on-shore and off-shore teams, running design and code reviews
Own data quality, SLAs, lineage, access control and cloud cost of delivered solutions
Apply DataOps/MLOps, Terraform and CI/CD in an Agile model
Design, build, test, and deploy data pipelines, analytics, and ML/GenAI solutions on Google Cloud
translate requirements into target-state data and AI architectures
Manage and mentor on-shore/off-shore teams, conduct design and code reviews
Own data quality, SLAs, lineage, access control, and cloud cost
Apply DataOps/MLOps, Terraform, automated testing, and CI/CD in an Agile model
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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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 – Associate Manager Management Level: 08-Associate Manager Location: All over India Must have skills Hands-on GCP Data & AI product delivery (design, build, run in production), not just custom development hosted on GCP. Strong Python and SQL skills; Java/Scala with Apache Beam is a plus. Deep GCP data engineering: BigQuery (partitioning, clustering, cost optimization), Dataflow, Pub/Sub, Dataproc, Cloud Composer/Dataform, Cloud Storage/BigLake, Datastream. Applied ML and GenAI on GCP: Vertex AI (Pipelines, Model Registry, Endpoints), BigQuery ML, Gemini, RAG, Vector Search, and agent frameworks (Agent Builder/ADK). Platform fundamentals: Terraform (IaC), CI/CD, DataOps/MLOps, observability, and security & governance (IAM, VPC Service Controls, CMEK, DLP, Dataplex). Domain depth in one or more of the Google Cloud Data & AI domains listed below. Strong offering mindset: solutioning, reusable assets, POVs, estimation, and value-based outcomes. Good to have Google Cloud Professional Data Engineer, ML Engineer, or Cloud Architect certification. Experience with Looker (LookML), Dataplex governance, and Analytics Hub data sharing. Experience leading on-shore/off-shore Agile teams. Job Summary As a Google Data & AI Engineer (Associate Manager), you will deliver data platforms, analytics, and AI solutions on Google Cloud, owning end-to-end execution from data ingestion and modelling to ML/GenAI and consumption. You will shape solutions with clients and Google partners, lead a small team, and ensure production-ready quality, security, reliability, performance, and cost. You will stay hands-on in architecture and development while driving DataOps/MLOps, CI/CD, and IaC. Roles & Responsibilities Hands-On Data & AI Engineering: Design, build, test, and deploy data pipelines, analytics, and ML/GenAI solutions on Google Cloud, from requirements to production support. Client-Facing Solutioning: Work with clients to understand business and data challenges, translate requirements into target-state data and AI architectures, and act as a trusted technical advisor. Team Leadership & Collaboration: Manage and mentor on-shore/off-shore teams, conduct design and code reviews, and collaborate with data owners, product, security, and business teams. Modern Engineering & Agile Delivery: Apply DataOps/MLOps, Terraform, automated testing, and CI/CD in an Agile model to deliver quality solutions at pace. Delivery Governance & FinOps: Own data quality, SLAs, lineage, access control, and cloud cost (BigQuery slots/reservations, storage tiers) of delivered solutions. Offerings & Growth: Contribute to POVs, reusable accelerators, reference architectures, estimates, and proposals that tie Google Data & AI capabilities to measurable business outcomes. Deliver outstanding results in one or more of these Google Cloud Data & AI domains: Data Platform & Modernization: Build and migrate enterprise warehouses and lakehouses to BigQuery/BigLake using Dataflow, Dataproc, Datastream, and Cloud Composer. Analytics & Business Intelligence: Deliver governed self-service analytics using Looker (LookML), BigQuery BI Engine, and Looker Studio. Generative & Agentic AI: Design and develop AI solutions using Vertex AI, Gemini, RAG, Vector Search, and multi-agent workflows. Applied ML & MLOps: Build, deploy, and monitor models using Vertex AI Pipelines, Feature Store, Model Registry, and BigQuery ML with automated retraining. Customer 360 & Marketing Intelligence: Unify customer data in GCP; use BigQuery and Vertex AI for identity resolution, predictive segments, and personalization. Real-Time & Streaming Analytics: Build event-driven pipelines with Pub/Sub, Dataflow, and BigQuery streaming for near-real-time insights. Data Governance & Security: Implement cataloging, lineage, quality, and policy controls with Dataplex, DLP, IAM, and VPC Service Controls. About Our Company | Accenture About Accenture
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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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