Google Cloud Platform Data Architect

Job Title: Google Cloud Data Architect IAM Data Modernization Location: Dallas, TX / Charlotte, NC/ Iselin, NJ, / Chandler, AZ (Hybrid 4 days office) Job Description Bachelors 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 workloads Familiarity with Gitbased source control, build automation, and deployment strategies Experience with OpenShift Container Platform (OCP) for deploying data workloads and services Understanding of containerized architecture, scaling, and environment management Proven ability to build CI/CD pipelines for data and infrastructure workloads Experience managing secrets securely using Google Cloud Platform Secret Manager Ownership of observability, SLOs, dashboards, alerts, and runbooks Proficiency in logging, monitoring, and alerting for data pipelines and platform reliability Handson experience with PySpark for ETL/ELT, data transformation, and performance optimization Solid understanding of distributed data processing concepts Strong experience designing data platforms on Google Cloud Platform (Google Cloud Platform) Experience with Data Lakes, data warehousing, and largescale migration programs Proven 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 controls Experience with Hadoop/HDFS architecture, distributed file systems, and data locality principles Hands-on experience with columnar data formats (Parquet, Avro, ORC) and compression techniques Expertise in partitioning strategies, backfills, and large-scale data organization Ability to design data models optimized for analytics and BI consumption Experience building batch and streaming ingestion pipelines using Google Cloud Platform-native services Knowledge of Pub/Sub-based streaming architectures, event schema design, and versioning Strong understanding of incremental ingestion and CDC patterns, including idempotency and deduplication Strong 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 design Experience managing schema evolution while minimizing downstream impact