Job Title
GCP Technical Architect Pre-Sales (Cloud & Data Engineering)
Location
APMEA
Experience
1016 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
