Job Summary :

We are seeking an experienced GCP Data Architect with deep multi-cloud expertise (AWS / Azure) to lead the architectural strategy, design, and implementation of our enterprise data platform. In this role, you will lead the migration, integration, and unification of complex data workloads across Google Cloud Platform and secondary cloud environments. You will bridge legacy architectures and hybrid multi-cloud systems into scalable, highly available, secure, and cost-efficient GCP data ecosystems.

Key Responsibilities :

1. Architecture & Strategy :

- Define the end-to-end multi-cloud and GCP data architecture strategy, target state architecture, and multi-year execution roadmap.

- Design robust data pipelines (batch & streaming), data lakes, and enterprise data warehouses using GCP-native services (BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage).

- Architect cross-cloud data movement strategies between AWS (S3, Redshift), Azure (ADLS, Synapse), and GCP while minimizing egress costs and latencies.

- Evaluate and implement modern data stack paradigms, including Data Mesh, Data Fabric, and Lakehouse architectures across heterogeneous cloud platforms.

2. Multi-Cloud & Hybrid Integration :

- Design secure inter-cloud networking and identity patterns (e.g., Anthos, BigQuery Omni, AWS VPC Peering, Azure ExpressRoute integration, Workload Identity Federation).

- Architect data ingestion models that handle high-volume, real-time data streaming from external cloud environments into GCP.

- Implement multi-cloud data virtualization, federation, and master data management (MDM) solutions.

3. Data Governance, Security & Compliance :

- Design and enforce enterprise-grade data security, access controls (IAM), key management (KMS), and compliance frameworks (HIPAA, GDPR, SOC 2) across multi-cloud environments.

- Implement automated data quality, cataloging, lineage tracking, and governance using tools like GCP Dataplex/Data Catalog or third-party tools (Collibra, Alation).

4. Technical Leadership & FinOps :

- Serve as the Subject Matter Expert (SME) for cloud data platforms, mentoring data engineers, MLOps specialists, and BI teams.

- Drive FinOps initiatives to optimize multi-cloud data storage and compute costs, particularly around BigQuery, Dataflow, and cross-cloud bandwidth charges.

- Establish CI/CD pipelines, Infrastructure-as-Code (Terraform), and DevOps/DataOps practices for cloud automated provisioning.

Required Qualifications :

- Experience : 6+ years in enterprise data architecture/engineering, with 4+ years specifically dedicated to GCP data solutions and 2+ years architecting multi-cloud or hybrid environments.

- Core GCP Stack :

1. Data Warehousing & Processing : BigQuery, BigQuery Omni, Dataflow (Apache Beam), Dataproc, Cloud Composer (Airflow).

2. Storage & Messaging : Cloud Storage (GCS), Pub/Sub, Cloud Bigtable, Cloud Spanner.

3. Security & Governance : GCP Dataplex, IAM, VPC Service Controls, Secret Manager.

- Multi-Cloud Proficiency :

1. Hands-on knowledge of AWS (S3, Glue, Redshift, Kinesis) or Azure (ADLS, Data Factory, Synapse, Databricks).

2. Direct experience with multi-cloud analytics capabilities like BigQuery Omni or Databricks Multi-Cloud.

- Languages & Automation :

1. Advanced SQL and Python or Scala.

2. Terraform / IaC and CI/CD pipelines (GitHub Actions, GitLab CI, Cloud Build).

- Data Modeling : Deep understanding of dimensional modeling, Data Vault, and relational DB designs (3NF).

Preferred Certifications :

- Google Cloud Certified Professional Data Engineer (Required / Strongly Preferred).

- Google Cloud Certified Professional Cloud Architect (Highly preferred).

Soft Skills :

- Strong stakeholder management skills with an ability to present complex architectural choices to executives.

- Demonstrated history of technical mentorship and cross-functional team leadership.

- Strong problem-solving skills for complex hybrid-cloud integration challenges.