AGBG Google Data & AI Engineer - Specialist (Lead)

Overview

Lead 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.

What you'll do

• Design, build, test and deploy complex data pipelines, analytics, and ML/GenAI solutions on Google Cloud across the full delivery lifecycle, from requirements gathering to production support.
• Work directly with clients to understand business and data challenges, translate requirements into technical designs, and act as technical advisor throughout the project.
• Lead and mentor on-shore and off-shore engineers, conduct design and code reviews, and collaborate with cross-functional stakeholders.
• 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 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 (LookML) and BigQuery.
• Contribute to the design and development of AI solutions using Vertex AI, Gemini models, and Retrieval-Augmented Generation (RAG).
• Build, deploy, and monitor ML models using Vertex AI Pipelines, Model Registry, and BigQuery ML.
• Unify customer data in GCP; use BigQuery and Vertex AI for predictive segments and personalization.
• Build event-driven pipelines with Pub/Sub, Dataflow, and BigQuery.
• Implement cataloging, lineage, quality, and access controls with Dataplex, DLP, and IAM.

What you'll need

• 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.
• 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 of: 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.

Nice to have

• Java/Scala with Apache Beam.
• 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.

Details

• Location: All over India.
• Management level: 09-Specialist.