G

Google

Runs Search and YouTube and builds Gemini AI

Training Delivery Senior Specialist - Webops, Web Analytics

Corporate & Technical TrainingConfirmed live in the last 24 hours
Full-timeHyderabad, Telangana, IndiaNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Information Technology, Data Analytics, Software Engineering, or a related technical discipline.
  • Seven to ten or more years of total experience, including at least four to five years of hands-on web analytics implementation and data engineering using advanced SQL on GCP BigQuery, and at least two to three years delivering technical training, facilitating bootcamps, or leading structured technical mentorship or enablement programs.
  • Experience implementing end-to-end website tagging strategies, validating data layers, and troubleshooting campaign performance.
  • Proficiency in advanced SQL, data manipulation, and building or maintaining ETL pipelines in GCP BigQuery.
  • Hands-on understanding of JavaScript, HTML, and CSS to audit, inspect, and troubleshoot website code and tracking scripts.
  • A foundation in adult learning principles and instructional design, and the ability to lead live coding and data debugging sessions.
  • Experience designing and deploying end-to-end tagging strategies using Google Tag Manager, Global Site Tag, and Google Analytics 4; understanding attribution modeling, cross-domain tracking, and headless or coupled CMS data-layer integration.
  • Ability to architect, query, and optimize large datasets using advanced SQL in GCP BigQuery; build and troubleshoot batch and streaming ETL pipelines; and understand OLAP concepts and data-warehousing design.
  • Ability to implement release management, error handling, system stability, and data-quality checks; apply large language models and prompt-engineering patterns to streamline data extraction, documentation, and technical problem-solving.
  • Ability to read and debug HTML5, CSS/CSS3, JavaScript, and basic PHP or server logic to diagnose tag execution failures, race conditions, and DOM changes.

Responsibilities

  • Deliver hands-on technical training sessions, live labs, bootcamps, and debug clinics in classroom and virtual formats.
  • Explain tracking, data collection, and pipeline architectures, including client-side and server-side Google Tag Manager, attribution models, BigQuery partition and cluster optimization, ETL pipeline debugging, and LLM prompt design.
  • Lead practical walkthroughs for building tagging strategies, validating data layers, peer-reviewing SQL queries, and optimizing campaign analytics.
  • Design, build, and update technical learning paths, hands-on lab exercises, and evaluation rubrics based on adult learning principles.
  • Create production-aligned exercises covering tag deployment, data warehouse modeling in BigQuery, and pipeline orchestration.
  • Develop implementation documentation templates, training modules, and best-practice guides for DataOps/DevOps release management.
  • Assess current-state skills across operations and engineering teams and build structured capability roadmaps.
  • Design and implement pre- and post-training assessments, practical data-modeling challenges, and tag audit simulations to measure skill acquisition.
  • Use learning metrics and operational performance data to evaluate program effectiveness, demonstrate return on investment, and optimize learning interventions.
  • Build relationships with Product Marketers, Senior Data Engineers, Technical Leads, and training partners to keep curricula aligned with business goals and industry standards.
  • Serve as the subject matter expert on Google's marketing and measurement ecosystem, BigQuery data warehousing, and modern data-layer architectures.

Desired Qualifications

  • Practical experience with large language models, prompt engineering, and translating business workflows into AI-augmented data solutions.
  • Experience with headless or decoupled content management systems such as Brightspot, Contentful, Strapi, Drupal, or AEM.
  • Experience with DataOps/DevOps practices, CI/CD code check-in workflows, and peer-reviewing production SQL queries.
  • Proficiency with data visualization tools such as Looker Studio, Tableau, or Power BI to present learning impact and analytics data.
  • Google Cloud certifications such as Professional Data Engineer or Cloud Digital Leader, or Google Analytics/Ads certifications.
  • Certifications in project management (Agile/Scrum or PMP) or process improvement (Six Sigma).

About the Company

Google

Runs Search and YouTube and builds Gemini AI

Google runs the world's most used search engine and free services such as YouTube, Android, and Gmail, and it builds the Gemini AI models that work inside them. In 2017, its researchers invented the transformer, the neural network design behind ChatGPT and most other AI chatbots. People use these services without paying, and Google earns most of its money from ads placed beside search results and YouTube videos. Businesses rent computing power and Gemini models through Google Cloud, and Google also sells subscriptions and Pixel phones. Larry Page and Sergey Brin founded Google in 1998 as Stanford PhD students; it is based in Mountain View, California, United States, and is the main business of parent company Alphabet.

Company size
10,001+
Company stage
IPO
Headquarters
Mountain View, CA
Founded
1998

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