GCP Architect

Job Title GCP Technical Architect – Pre-Sales (Cloud & Data Engineering) Location APMEA Experience 10–16 years (Cloud, Data Platforms, and Customer-Facing Architecture) Role Overview The GCP Technical Architect – Pre-Sales (Cloud & Data Engineering) owns end-to-end solution architecture, data platform design, and technical strategy during the sales lifecycle. The role partners with Sales, Business Development, Google teams, and Delivery to craft secure, scalable, and cost-optimized cloud and data architectures on Google Cloud, helping customers modernize applications and unlock value from data. This role is critical in positioning cloud-native data platforms, analytics, and AI-ready architectures while ensuring commercial viability and delivery readiness. Key Responsibilities Pre-Sales & Customer Engagement • Own technical discovery, architecture definition, and solution storytelling for cloud and data-led deals • Translate business use cases into GCP-based cloud and data architectures • Engage with CXOs, Chief Data Officers, Architects, and Engineering leaders • Lead RFP/RFI responses covering cloud infrastructure, data platforms, and analytics • Deliver technical presentations, demos, and PoCs for cloud modernization and data engineering use cases Cloud & Data Solution Architecture Cloud Platform Architecture • Design end-to-end GCP architectures across: • Compute: GCE, GKE, Cloud Run, App Engine • Networking: VPCs, Shared VPC, Interconnect, VPN, Load Balancing • Security: IAM, KMS, Secret Manager, VPC-SC, Security Command Center • Architect hybrid and multi-cloud solutions (on-prem ↔ GCP, AWS/Azure ↔ GCP) • Apply Well-Architected Framework principles across security, reliability, performance, cost, and operations Data Engineering & Analytics Architecture • Design modern data platforms on GCP, including: • Data ingestion & streaming: Pub/Sub, Dataflow, Dataproc • Data lakes & storage: Cloud Storage, BigLake • Data warehousing & analytics: BigQuery • Operational databases: Cloud SQL, Spanner, Firestore, Bigtable • Architect batch and real-time data pipelines with scalability, reliability, and governance in mind • Define data modeling, partitioning, clustering, and performance optimization strategies in BigQuery • Design data governance, security, and lineage using IAM, DLP, Dataplex, and cataloging capabilities • Enable AI/ML-ready data architectures for downstream analytics, BI, and machine learning workloads Cost, FinOps & Commercial Support • Build TCO, ROI, and cost models for cloud infrastructure and data platforms • Advise on FinOps practices for BigQuery, Dataflow, storage tiers, and streaming workloads • Optimize architectures for performance vs. cost trade-offs • Partner with Sales to align scope, commercials, and assumptions Delivery Alignment & Governance • Ensure clean handover from pre-sales to delivery teams • Define migration and modernization roadmaps (apps + data) • Identify architectural risks early and define mitigation strategies • Provide architectural oversight during early delivery phases • Mentor delivery teams on cloud and data best practices Required Skills & Experience GCP & Cloud Engineering • Deep hands-on experience with core GCP services • Strong knowledge of Kubernetes (GKE), microservices, CI/CD, and IaC (Terraform) • Expertise in cloud networking and security design Data Engineering & Analytics • Strong experience designing enterprise-scale data platforms • Expertise in BigQuery architecture, performance tuning, and cost optimization • Experience with batch and streaming pipelines • Understanding of data governance, compliance, and data quality frameworks Architecture & Consulting • Proven experience in enterprise solutioning and pre-sales architecture • Strong understanding of data and application modernization patterns • Ability to balance technical depth with business and commercial realities Stakeholder Communication • Strong whiteboarding, storytelling, and executive communication skills • Ability to explain complex data architectures to non-technical stakeholders • Excellent documentation and proposal-writing skills Certifications (Preferred) • Google Professional Cloud Architect • Google Professional Data Engineer • Google Professional Cloud Security Engineer • Kubernetes / DevOps certifications (plus) Nice to Have • Experience working with Google partner ecosystem and Google field teams • Exposure to regulated industries (BFSI, Healthcare, Public Sector) • Experience with AI/ML platforms, MLOps, and GenAI data foundations Success Metrics • Win rate and deal value for cloud + data-led opportunities • Customer confidence in proposed cloud and data architectures • Minimal architecture rework during delivery • Strong alignment between data strategy, cloud platform, and business outcomes