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Mumbai · On-site · 6-9 Yrs · Oct 12
Internet & Web Services · 10000+ Employees · Mountain View, US
Since our founding in 1998, Google has grown by leaps and bounds. Starting from two computer science students in a university dorm room, we now have over a hundred thousand employees and over one hundred offices around the world. These Googlers build products that help create opportunities for everyone, whether down the street or across the globe. So whether you want to be a part of developing innovative technology, campaigns, products or partnerships, your work here is a chance to accomplish things that matter. To learn more about our job opportunities, teams, offices, benefits and workplace culture, visit careers.google.com.
Hiring: Engineering
What employees say
+ Great Work Life balance. Great compensation and benefits. You get learn from the code that runs highly sophisticated Google Products.
− I could not find any cons as such.
More reviews on the company profile.
Interview experience · Intern
Interview was DSA heavy and asked some System Design concepts too. They asked 2 DSA question in DSA round of medium and hard difficulty. After that they asked CS Fundamentals in further round too and CGPA criteria was 7
Difficult difficulty · India · 2,830 reports
More interview insightsJob description
Overview
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Bengaluru, Karnataka, India; Mumbai, Maharashtra, India. Minimum qualifications:
Responsibilities
- Define technical strategy for large accounts, engaging C-level executives via live demonstrations to solve business problems using the Agentic Data Cloud.
- Design, code, and deploy production-grade Data + AI pipelines (e.g., fraud detection, recommendation engines) and map legacy data estates to open-format architectures (Apache Iceberg).
- Orchestrate Intent-Driven data engineering to autonomously deploy PySpark pipelines using the Data Agent Kit, Antigravity, and Model Context Protocol.
- Lead high-impact showcases and technical value validations using BigQuery, Borderless Lakehouse, Knowledge Catalog, Spark, and Vertex AI to prove business outcomes.
- Conduct detailed Total Cost of Ownership (TCO) analyses and optimize architectures (such as balancing DRAM/SSD, compute shapes, and token spend) to prevent runaway costs on the Lightning Engine.
Qualifications
- Bachelor's degree or equivalent practical experience.
- 6 years of experience as a data or systems engineer, solutions architect, or pre-sales consultant.
- Experience delivering demos, workshops, or architect overviews to business leaders.
- Experience migrating, refactoring, or debugging proprietary or open source workloads.
- Experience building data platforms, warehouses, or data lakes, and experience with data programming languages and leveraging agentic platforms.
- Ability to communicate in English fluently to manage stakeholder relationships.
Nice to have
- Experience designing and deploying enterprise Retrieval-Augmented Generation (RAG) pipelines, Large Language Model (LLM) application integrations, or context orchestration frameworks.
- Experience implementing enterprise data/AI governance, metadata management, access control, or lineage tracking across modern catalogs.
- Experience with developer advocacy, building internal technical programs, delivering technical enablement, or contributing to open-source data/AI communities.
- Experience in core data science workflows, including proficiency with data manipulation libraries and integrating data pipelines with ML platforms.
- Experience applying value-selling principles to align technical architectures with business outcomes.
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Job application FAQ
Last updated 17 October 2026
- How do I apply for Data Analytics Customer Engineer, Google Cloud (English) at Google?
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- Is Data Analytics Customer Engineer, Google Cloud (English) remote or on-site in Mumbai, Maharashtra?
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- What skills matter for this Data Analytics Customer Engineer, Google Cloud (English) role at Google?
- This is a mid-level Data Analytics Customer Engineer, Google Cloud (English) role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.