Lead specialist who drives client‑facing delivery of data, analytics, and AI solutions on Google Cloud, mentoring teams and shaping repeatable offerings.
Locations (2)
Bengaluru, Karnataka, India
India
Responsibilities
Design, build, test, and deploy complex data pipelines, analytics, and ML/GenAI solutions on Google Cloud
Translate client requirements into technical designs and act as a technical advisor
Lead and mentor on‑shore and off‑shore engineers, conduct design and code reviews
Apply DataOps/MLOps practices and Infrastructure as Code within an Agile framework
Build accelerators, reference architectures, and POVs that make Google Data & AI delivery repeatable
Requirements
Nice to have: Google Cloud Professional Data Engineer certification
Nice to have: Google Cloud Professional Machine Learning Engineer certification
Nice to have: Looker governance
AGBG Google Data & AI Engineer - Specialist (Lead)
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.
Responsibilities
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.
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.
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.
Apply DataOps/MLOps practices and Infrastructure as Code (Terraform) within an Agile framework to deliver high-quality solutions at pace.
Build accelerators, reference architectures, and POVs that make Google Data & AI delivery repeatable and tied to measurable outcomes.
Requirements
Nice to have: Java
Nice to have: Scala
Nice to have: Apache Beam
Nice to have: Google Cloud Professional Data Engineer certification
Nice to have: Google Cloud Professional Machine Learning certification
Lead client‑facing delivery of data, analytics, and AI solutions on Google Cloud, driving end‑to‑end engineering, mentoring teams, and shaping repeatable offerings.
Locations (2)
Bengaluru, Karnataka, India
India
Responsibilities
Design, build, test, and deploy complex data pipelines, analytics, and ML/GenAI solutions on Google Cloud
Translate client requirements into technical designs and act as a technical advisor
Lead and mentor on‑shore and off‑shore engineers, conduct design and code reviews
Apply DataOps/MLOps practices and Infrastructure as Code within an Agile framework
Build accelerators, reference architectures, and POVs that make delivery repeatable
Requirements
Nice to have: Google Cloud Professional Data Engineer certification
Nice to have: Google Cloud Professional Machine Learning Engineer certification
Nice to have: Experience mentoring engineers in an on‑shore/off‑shore Agile delivery model
A technical bridge between product and customers' data infrastructure, designing, implementing, and optimizing semantic layer architectures to solve complex data challenges.
Responsibilities
Design and architect end-to-end semantic layer solutions using Cube, integrating with customers' existing data warehouses (Snowflake, BigQuery, Redshift).
Build comprehensive data models in YAML or JavaScript that define metrics, dimensions, and business logic.
Develop proof-of-concepts and technical demonstrations on customer data, and lead technical discovery sessions to understand data architecture and requirements.
Guide customers on best practices for data modeling, caching strategies, access control, and performance optimization.
Run hands-on workshops and training to enable customer teams, and partner with Sales to provide technical expertise during the evaluation process.
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