{"schemaVersion":"jobsearcher.job.v1","id":"b6ed51303dadb9c6d89c6cfb","url":"https://jobsearcher.com/jobs/b6ed51303dadb9c6d89c6cfb","canonicalUrl":"https://jobsearcher.com/jobs/b6ed51303dadb9c6d89c6cfb","title":"GCP Spanner Data Engineer","description":"Overview:\nProdapt is the largest specialized player in the Connectedness industry. As an AI-first strategic technology partner, Prodapt provides consulting, business reengineering, and managed services for the largest telecom and tech enterprises building networks and digital experiences of tomorrow. A ServiceNow-invested company, Prodapt has been recognized by Gartner as a Large, Telecom-Native, Regional IT Service Provider. A “Great Place To Work® Certified™” company, Prodapt employs over 6,000 technology and domain experts across the Americas, Europe, India, Africa, & Japan. Prodapt is part of the 130-year-old business conglomerate The Jhaver Group, which employs over 32,000 people across 80+ locations globally.\nLooking for a seasoned GCP Data Engineer to design, build, and maintain large-scale data pipelines and infrastructure on Google Cloud Platform. You will work closely with data architects, analysts, and product teams to deliver reliable, performant, and cost-efficient data solutions.\nResponsibilities:\nDesign and implement scalable data pipelines using GCP-native services (Dataflow, Dataproc, Pub/Sub, Cloud Composer/Airflow)\nArchitect and optimize BigQuery datasets, tables, and queries for analytical workloads at scale\nDesign and manage Cloud Spanner schemas for globally distributed, strongly consistent transactional data\nBuild and maintain data models, transformations, and orchestration workflows using Cloud Workflows and related tools\nDevelop backend data services and ETL/ELT scripts in Python\nIntegrate and manage Firestore for real-time, document-oriented data use cases\nDesign and manage the GraphQL schema\nBuild highly optimized resolver functions that bridge the GraphQL schema directly to data warehouses\nImplement GraphQL Subscriptions to stream live data, event changes, or real-time metrics using message brokers like Apache Kafka\nImplement data governance, lineage, and quality frameworks using tools like Dataplex or Data Catalog\nCollaborate on infrastructure-as-code using Terraform for GCP resource provisioning\nMonitor pipeline health, optimize costs, and troubleshoot production issues\nMentor junior engineers and contribute to architectural decisions and best practices\nRequirements:\nBachelor’s degree in Computer Science, Engineering, or a related field; OR equivalent combination of education and relevant experience.\n10+ years of overall experience in data engineering or a related field\n5+ years of hands-on experience on Google Cloud Platform\nStrong proficiency in Python for data processing, automation, and pipeline development\nDeep expertise in BigQuery — schema design, partitioning, clustering, query optimization, cost governance\nProduction experience with Cloud Spanner — schema design, interleaving, transaction patterns, and performance tuning\nSolid understanding of GCP data services: Dataflow, Pub/Sub, Cloud Storage, Dataproc, Cloud Composer\nExperience with Cloud Workflows for serverless orchestration\nHands-on experience with Firestore (Native mode preferred) for NoSQL/document storage patterns\nStrong SQL skills and understanding of data warehousing concepts\nExperience with CI/CD pipelines (Cloud Build, GitHub Actions) and version control (Git)\n\nPreferred / Nice to Have\nExperience with dbt for transformation layer on BigQuery\nFamiliarity with streaming architectures (exactly-once semantics, late data handling)\nKnowledge of data mesh or data lakehouse patterns\nExposure to Vertex AI or ML pipelines for MLOps workflows\nGCP Professional Data Engineer certification","company":"Prodapt","rawCompany":"prodapt","city":"Richardson","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-06-26T13:51:43.685Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"GCP Spanner Data Engineer","description":"Overview:\nProdapt is the largest specialized player in the Connectedness industry. As an AI-first strategic technology partner, Prodapt provides consulting, business reengineering, and managed services for the largest telecom and tech enterprises building networks and digital experiences of tomorrow. A ServiceNow-invested company, Prodapt has been recognized by Gartner as a Large, Telecom-Native, Regional IT Service Provider. A “Great Place To Work® Certified™” company, Prodapt employs over 6,000 technology and domain experts across the Americas, Europe, India, Africa, & Japan. Prodapt is part of the 130-year-old business conglomerate The Jhaver Group, which employs over 32,000 people across 80+ locations globally.\nLooking for a seasoned GCP Data Engineer to design, build, and maintain large-scale data pipelines and infrastructure on Google Cloud Platform. You will work closely with data architects, analysts, and product teams to deliver reliable, performant, and cost-efficient data solutions.\nResponsibilities:\nDesign and implement scalable data pipelines using GCP-native services (Dataflow, Dataproc, Pub/Sub, Cloud Composer/Airflow)\nArchitect and optimize BigQuery datasets, tables, and queries for analytical workloads at scale\nDesign and manage Cloud Spanner schemas for globally distributed, strongly consistent transactional data\nBuild and maintain data models, transformations, and orchestration workflows using Cloud Workflows and related tools\nDevelop backend data services and ETL/ELT scripts in Python\nIntegrate and manage Firestore for real-time, document-oriented data use cases\nDesign and manage the GraphQL schema\nBuild highly optimized resolver functions that bridge the GraphQL schema directly to data warehouses\nImplement GraphQL Subscriptions to stream live data, event changes, or real-time metrics using message brokers like Apache Kafka\nImplement data governance, lineage, and quality frameworks using tools like Dataplex or Data Catalog\nCollaborate on infrastructure-as-code using Terraform for GCP resource provisioning\nMonitor pipeline health, optimize costs, and troubleshoot production issues\nMentor junior engineers and contribute to architectural decisions and best practices\nRequirements:\nBachelor’s degree in Computer Science, Engineering, or a related field; OR equivalent combination of education and relevant experience.\n10+ years of overall experience in data engineering or a related field\n5+ years of hands-on experience on Google Cloud Platform\nStrong proficiency in Python for data processing, automation, and pipeline development\nDeep expertise in BigQuery — schema design, partitioning, clustering, query optimization, cost governance\nProduction experience with Cloud Spanner — schema design, interleaving, transaction patterns, and performance tuning\nSolid understanding of GCP data services: Dataflow, Pub/Sub, Cloud Storage, Dataproc, Cloud Composer\nExperience with Cloud Workflows for serverless orchestration\nHands-on experience with Firestore (Native mode preferred) for NoSQL/document storage patterns\nStrong SQL skills and understanding of data warehousing concepts\nExperience with CI/CD pipelines (Cloud Build, GitHub Actions) and version control (Git)\n\nPreferred / Nice to Have\nExperience with dbt for transformation layer on BigQuery\nFamiliarity with streaming architectures (exactly-once semantics, late data handling)\nKnowledge of data mesh or data lakehouse patterns\nExposure to Vertex AI or ML pipelines for MLOps workflows\nGCP Professional Data Engineer certification","datePosted":"2026-06-26T13:51:43.685Z","dateModified":"2026-06-26T13:51:43.685Z","hiringOrganization":{"@type":"Organization","name":"Prodapt","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Richardson","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"b6ed51303dadb9c6d89c6cfb"},"url":"https://jobsearcher.com/jobs/b6ed51303dadb9c6d89c6cfb"}}