GCP Analytics Platform Architect

Role: Platform Architect

Required Skills: Data architect

Qualification: BACHELOR OF COMPUTER SCIENCE

Experience: 12 - 17 Years

Function: TECHNOLOGY

Apply By: 2027-01-02

Must Have Technical/Functional Skills

Experience: 12+ years of experience in GCP Data Architecture & ETL/ELT pipeline creation,

BigQuery, Cloud Platforms or Data Engineering, with at least 5 years as an Architect.

Strong programming in Python and Java; query & storage optimization.

Cloud Proficiency: Deep expertise in BigQuery, Cloud Storage (GCS), and data

orchestration (Cloud Composer / Airflow). Data processing using Dataflow, Dataproc, and

microservices. Strong experience with at least one major cloud provider (AWS, GCP, or

Azure) and their managed Kubernetes offerings.

GenAI & Platform: Practical application development using Gemini Enterprise, Vertex AI,

and RAG concepts. Foundation in DevOps (Docker, GKE, CI/CD, IAM).

Kubernetes Mastery: Deep, hands-on experience managing production Kubernetes

environments, including cluster scaling, RBAC, network plugins (CNI), and storage (CSI).

Deployment Tooling: Proven track record of designing complex deployments using Helm

and GitOps controllers (ArgoCD/Flux).Scripting & Automation: Proficiency in at least one

programming or scripting language (Python, Go, or Bash) for automation and tooling.

Roles & Responsibilities

We are seeking a highly skilled GCP Architect to lead the architecture, design, and development of GCP based Analytics Platform. In this role, you will be the cornerstone of finalizing the Technical approach, design, data discovery, data transformation, Analytics Platform development and closely work with the Business team to fine tune the requirements, and ensure development of scalable Analytics platform that is capable to perform all scenarios incl 'What-if' analysis and and "Agentic AI-driven consumption"

Key Responsibilities

Analytics Platform Architecture & Design

Design Strategies: Architect and implement scalable, secure, GCP-native Analytics Platform supporting microservices and data-intensive workloads.

Data Engineering: Discover, integrate, build, and maintain advanced ETL/ELT data pipelines (Dataflow, Dataproc, Cloud Composer/Airflow) migrating legacy Oracle data structures into BigQuery-based analytical models.

Query & Storage Optimization: Design BigQuery schemas, partitioning, clustering, and materialized views to support high-performance analytics and "What-If" scenario modeling.

GenAI Integration: Architect and develop analytics capabilities using Gemini Enterprise, Vertex AI, and RAG patterns, ensuring the platform is readily consumable by Agentic AI agents for automated insights and decision support.

Microservices Development: Design and build Python/Java-based microservices exposing analytics APIs and data products to downstream applications and AI agents.

Business & Stakeholder Collaboration

Work closely with Business stakeholders to translate analytics and "What-If" scenario requirements into technical architecture.

Lead architecture discussions during customer/client workshops on Oracle-to-GCP transformation strategy.

Kubernetes Ecosystem Management

Cluster Lifecycle: Provision, upgrade, and manage productio n-grade Kubernetes clusters (e.g., EKS, GKE, AKS, or bare metal).

K8s Configuration: Develop and maintain Helm charts, Kustomize manifests, and custom resource definitions (CRDs) for complex application requirements.

Traffic & Networking: Architect ingress controllers, service meshes (e.g., Istio, Linkerd), and network policies to ensure secure and efficient internal and external traffic routing.

Storage & Stateful Loads: Design and manage persistent volumes and stateful sets for applications requiring durable storage.

Infrastructure & Reliability

Infrastructure as Code (IaC): Automate the provisioning of underlying cloud resources using Terraform, Pulumi, or Ansible.

Observability: Implement comprehensive monitoring, logging, and tracing solutions (e.g., Prometheus, Grafana, ELK stack, Datadog, OpenTelemetry) to track deployment health and application performance.

Educational & Certification Requirements

Certifications: GCP Professional Data Engineer or GCP Professional Cloud Architect certification.

Service Mesh: Practical experience implementing and managing service meshes for MTLS and advanced traffic shaping.

Security: Experience with container vulnerability scanning, OPA Gatekeeper, or Kyverno for policy enforcement.

Bachelors in Computer science or IT or any Engineering

TCS Employee Benefits Summary

Discretionary Annual Incentive.

Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.

Family Support: Maternal & Parental Leaves.

Insurance Options: Auto & Home Insurance, Identity Theft Protection.

Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.

Time Off: Vacation, Time Off, Sick Leave & Holidays.

Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

Salary Range: $130,000-$150,000 a year