Google Cloud Platform Data Architect

Job Title: Google Cloud Data Architect IAM Data ModernizationLocation: Dallas, TX / Charlotte, NC/ Iselin, NJ, / Chandler, AZ (Hybrid 4 days office)Job DescriptionBachelors or relevant degree with 10 14+ years in DevOps and Data Architecture, 5+ years designing on Pyspark/Google Cloud Platform/OCP at scale; prior on prem cloud migration a must.Certifications: Google Cloud Professional Cloud Architect/DevOps/OCP (required or within 3 months). Plus: Professional Data Engineer, Security Engineer.Experience implementing CI/CD pipelines for data and analytics workloadsFamiliarity with Gitbased source control, build automation, and deployment strategiesExperience with OpenShift Container Platform (OCP) for deploying data workloads and servicesUnderstanding of containerized architecture, scaling, and environment managementProven ability to build CI/CD pipelines for data and infrastructure workloadsExperience managing secrets securely using Google Cloud Platform Secret ManagerOwnership of observability, SLOs, dashboards, alerts, and runbooksProficiency in logging, monitoring, and alerting for data pipelines and platform reliabilityHandson experience with PySpark for ETL/ELT, data transformation, and performance optimizationSolid understanding of distributed data processing conceptsStrong experience designing data platforms on Google Cloud Platform (Google Cloud Platform)Experience with Data Lakes, data warehousing, and largescale migration programsProven experience designing and implementing data lake architectures (e.g., Bronze/Silver/Gold or layered models).Strong knowledge of Cloud Storage (GCS) design, including bucket layout, naming conventions, lifecycle policies, and access controlsExperience with Hadoop/HDFS architecture, distributed file systems, and data locality principlesHands-on experience with columnar data formats (Parquet, Avro, ORC) and compression techniquesExpertise in partitioning strategies, backfills, and large-scale data organizationAbility to design data models optimized for analytics and BI consumptionExperience building batch and streaming ingestion pipelines using Google Cloud Platform-native servicesKnowledge of Pub/Sub-based streaming architectures, event schema design, and versioningStrong understanding of incremental ingestion and CDC patterns, including idempotency and deduplicationStrong proficiency in BigQuery SQL, including query optimization, partitioning, clustering, and cost control.Hands-on experience with Hadoop MapReduce and ecosystem tools (Hive, Pig, Sqoop)Advanced Python programming skills for data engineering, including testing and maintainable code designExperience managing schema evolution while minimizing downstream impact