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Ernst & Young

Global professional services: consulting, assurance, tax

DE-Cloud Native AI and Data Engineer-GCP-GDSN02

Data EngineeringPosted on Nov 12
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • Strong hands-on experience in data engineering, cloud-native engineering, and production-grade AI/ML solution delivery on Google Cloud.
  • Practical experience with Vertex AI, including model development or integration, deployment patterns, and use-case-driven implementation for enterprise or industry scenarios.
  • Ability to build and optimize ETL and data pipelines using Python, Java, Go, or Scala, and execute workloads on Spark, Flink, and Google Cloud Dataflow.
  • Working knowledge of GenAI integration patterns for automation, insight generation, predictive analytics, and intelligent data workflows.
  • Understanding of token economics for GenAI solutions, including prompt design efficiency, token consumption, latency, cost optimization, usage monitoring, and governance considerations.
  • Awareness of multi-cloud deployment patterns and ability to translate data engineering, AI/ML, and GenAI solution architectures from Google Cloud to Microsoft Azure where client environments require it.
  • Basic to working knowledge of Microsoft Azure cloud services relevant to data platforms, AI/ML workloads, GenAI-enabled applications, and cloud-native deployment.
  • Strong programming skills in Java, Python, Go, and scripting languages, with ability to troubleshoot and optimize application and data-processing components.
  • Good understanding of application and container lifecycle management, including containerized deployment, operational readiness, and supportability.
  • Experience setting up CI/CD pipelines for build, validation, and target platform deployment.
  • Professional or Practitioner-level Google Cloud certification and demonstrated hands-on public cloud delivery experience.
  • Strong analytical thinking, problem-solving ability, and a structured approach to escalation, documentation, and knowledge sharing.
  • Clear communication skills and ability to collaborate with product, data, platform, and engineering teams in a delivery-focused environment.
  • Professional or Practitioner certification on Google Cloud is required.

Responsibilities

  • Design, build, and optimize scalable data pipelines and ETL workflows using Python, Java, Go, or Scala, and run them on Apache Flink, Apache Spark, and Google Cloud Dataflow.
  • Build cloud-native AI/ML solutions using Vertex AI for industry-specific use cases, describing the supported business use case, data flow, model lifecycle, and measurable outcome.
  • Integrate GenAI capabilities with data pipelines to enhance automation, insight generation, predictive analytics, and intelligent data processing across enterprise platforms.
  • Apply token economics principles to GenAI-enabled solutions, including prompt optimization, token usage monitoring, cost control, latency management, and performance trade-off assessment.
  • Stay current with emerging AI and GenAI technologies and identify practical ways to embed GenAI-driven intelligence into modern data platforms.
  • Design reusable solution patterns for data engineering, AI/ML, and GenAI workloads, primarily on Google Cloud and adaptable for Microsoft Azure when required.
  • Develop and maintain application components and automation scripts using Java, Python, Go, and scripting languages.
  • Manage the complete application and container lifecycle, including build, packaging, deployment, monitoring, troubleshooting, and support.
  • Apply public cloud engineering practices, with hands-on expertise in Google Cloud.
  • Demonstrate working knowledge of Microsoft Azure services to support deployment of similar data, AI/ML, and GenAI solution architectures across client cloud environments.
  • Set up and maintain CI/CD pipelines for application builds and target platform deployments.
  • Escalate unresolved issues to appropriate internal engineering teams using clear problem statements and supporting diagnostics.
  • Document technical knowledge, deployment steps, support notes, and operating procedures as reusable notes, runbooks, and manuals.
  • Allocate personnel, supervise team members, assign tasks, ensure the team has necessary tools and support, and optimize and evaluate team performance to meet organizational goals.
  • Make decisions, optimize processes, manage resources, and oversee team management as needed for task execution.

Desired Qualifications

  • Experience with Apache Beam and Java/Spring Boot for pipeline and application development.
  • Familiarity with Google Cloud certifications such as Professional Cloud Architect or Data Engineer.
  • Microsoft Certified: Azure Solutions Architect Expert (AZ-305).
  • Experience with CI/CD platforms such as GitHub Actions, Jenkins, or Azure DevOps.
  • Familiarity with AI-assisted development tools such as GitHub Copilot or similar.

About the Company

Ernst & Young

Global professional services: consulting, assurance, tax

EY (Ernst & Young) provides professional services at a global scale, offering consulting, assurance, tax, and transaction advisory services. It serves clients across industries such as technology, media, real estate, hospitality, and construction. Instead of selling a single product, EY works with clients through tailored engagements where cross-disciplinary teams analyze challenges, design strategies, perform audits, help with tax planning, and assist with mergers or divestitures. What sets EY apart is its worldwide reach and integrated service model, industry-specific expertise, and focus on responsible business practices like sustainability, cybersecurity, and workforce flexibility. EY’s goal is to help organizations improve performance, manage risk, and achieve sustainable growth while building a better working world.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Boston, MA
Founded
1991

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