AGBG Google Data & AI Engineer - Associate Manager

Overview

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, while leading a small on-shore/off-shore team.

What you'll do

• Design, build, test, and deploy data pipelines, analytics, and ML/GenAI solutions on Google Cloud, from requirements to production support.
• 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.
• Manage and mentor on-shore/off-shore teams, conduct design and code reviews, and collaborate with data owners, product, security, and business teams.
• Apply DataOps/MLOps, Terraform, automated testing, and CI/CD in an Agile model to deliver quality solutions at pace.
• Own data quality, SLAs, lineage, access control, and cloud cost (BigQuery slots/reservations, storage tiers) of delivered solutions.
• Contribute to POVs, reusable accelerators, reference architectures, estimates, and proposals that tie Google Data & AI capabilities to measurable business outcomes.
• Build and migrate enterprise warehouses and lakehouses to BigQuery/BigLake using Dataflow, Dataproc, Datastream, and Cloud Composer.
• Deliver governed self-service analytics using Looker (LookML), BigQuery BI Engine, and Looker Studio.
• Design and develop AI solutions using Vertex AI, Gemini, RAG, Vector Search, and multi-agent workflows.
• Build, deploy, and monitor models using Vertex AI Pipelines, Feature Store, Model Registry, and BigQuery ML with automated retraining.
• Unify customer data in GCP; use BigQuery and Vertex AI for identity resolution, predictive segments, and personalization.
• Build event-driven pipelines with Pub/Sub, Dataflow, and BigQuery streaming for near-real-time insights.
• Implement cataloging, lineage, quality, and policy controls with Dataplex, DLP, IAM, and VPC Service Controls.

What you'll need

• Hands-on GCP Data & AI product delivery (design, build, run in production), not just custom development hosted on GCP.
• Strong Python and SQL skills.
• 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: Data Platform & Modernization, Analytics & Business Intelligence, Generative & Agentic AI, Applied ML & MLOps, Customer 360 & Marketing Intelligence, Real-Time & Streaming Analytics, Data Governance & Security.
• Strong offering mindset: solutioning, reusable assets, POVs, estimation, and value-based outcomes.

Nice to have

• Java/Scala with Apache Beam.
• 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.

Details

• Location: All over India; posting location line lists Bengaluru.
• Management level: 08-Associate Manager.