GCP Data & Integration Architect

Job Designation: GCP Data & Integration Architect (Provider Data Management) Location - Gurgaon/Bangalore (WFO)- 5 days onsite Budget:35LPA Experience- 10+yrs Immediate joiner's or 1 week notice not more than that. Role OverviewWe are seeking a highly skilled, hands-on GCP Architect to lead the design and implementation of a scalable, real-time data integration ecosystem supporting enterprise provider data management. This role will play a critical part in establishing trusted, governed data products and modern data platform capabilities in alignment with a cloud-first architecture.The ideal candidate combines deep engineering expertise with architectural leadership, bringing the ability to design high-performance systems, guide cross-functional teams, and ensure scalable, production-grade implementation patterns. Key Responsibilities Architecture & Solution Design Define and implement end-to-end data architecture leveraging GCP services (BigQuery, Dataflow, Pub/Sub, GCS, etc.)Design scalable ingestion frameworks supporting batch, CDC, and event-driven integrationsEstablish real-time data pipelines and streaming architectures using Kafka and cloud-native servicesDevelop data product-oriented architectures with reusable, governed datasets and clear consumption patternsDrive architecture for master data management (MDM) and canonical data models to enable a unified provider identity Data Engineering & Platform Enablement Architect and optimize distributed data processing pipelines using Spark and PythonImplement orchestration frameworks (e.g., Airflow) to support robust, scalable pipeline operationsEnable real-time synchronization and event-driven integration patterns across enterprise systemsDesign systems for high data quality, lineage, metadata management, and governanceSupport implementation of lakehouse architectures (bronze/silver/gold data layers)Cloud & Platform Strategy Lead architecture across multi-cloud environments (GCP + Azure) with clear abstraction and portability principlesDefine and enforce cloud-native best practices, including cost optimization, security, and observabilityImplement infrastructure-as-code (Terraform or equivalent) and CI/CD pipelines for automated deliveryEnable containerized deployments and orchestration using Docker and KubernetesEngineering Leadership & CollaborationPartner with engineering teams to set technical direction, review designs, and guide implementationEstablish scalable design patterns and reusable frameworks across integration and data platform componentsProvide hands-on support for complex technical challenges and performance optimizationCollaborate across product, architecture, and operations teams to ensure aligned and sustainable delivery Required Qualifications 10+ years of experience in data architecture, data engineering, or distributed systemsDeep expertise in GCP data ecosystem (BigQuery, Dataflow, Pub/Sub, Dataproc, GCS)Strong experience with:Kafka / streaming platformsApache Spark (batch and streaming)Python developmentAirflow or equivalent orchestration toolsProven track record designing and delivering:Real-time integration architecturesLarge-scale data platforms handling high-volume dataStrong understanding of:Data modeling, data warehousing, and lakehouse architectureMetadata management, governance, and data quality frameworks Experience with:Microservices and event-driven architectureDocker / KubernetesCI/CD pipelines and DevOps practicesInfrastructure-as-code (Terraform, Cloud deployment frameworks) Preferred Qualifications Experience implementing enterprise MDM solutions or data product architecturesFamiliarity with data cataloging and governance tools (e.g., Atlan, Collibra, Informatica)Exposure to healthcare data environments (not required but beneficial)Experience working in fast-paced, transformation-driven environments with ambiguous requirementsLeadership & Ways of WorkingStrong ability to operate as a hands-on architect while guiding broader teamsComfortable influencing senior stakeholders and cross-functional teamsDemonstrated ability to balance speed, scalability, and governance in solution designThrives in environments requiring structured problem solving and iterative delivery .