{"schemaVersion":"jobsearcher.job.v1","id":"ac7d1897f55611ffcdae9e76","url":"https://jobsearcher.com/jobs/ac7d1897f55611ffcdae9e76","canonicalUrl":"https://jobsearcher.com/jobs/ac7d1897f55611ffcdae9e76","title":"Data Engineer, Analytics","description":"Senior GCP Data Engineer (ML & Fraud Analytics Data Platform)Location: Austin TX (100% Onsite)Skills Required: GCP, BigQuery, Python, Dataflow, Composer/Airflow, Google Cloud Storage (GCS)Key Responsibilities & SkillsDesign, develop, and maintain scalable ETL/data pipelines on GCP using Python, Dataflow, BigQuery, Cloud Storage, Composer/Airflow, and Control-M to support fraud analytics, ML, and enterprise data initiatives.Build and optimize ML-ready datasets, feature engineering pipelines, and reusable data assets for model training, validation, and production deployment.Develop high-quality Python solutions following coding standards, security best practices, resiliency, reliability, and performance optimization principles.Strong expertise in SQL, BigQuery/PostgreSQL, data modelling, database concepts, and large-scale data processing.Implement data quality, reconciliation, lineage, metadata management, governance, and monitoring controls to ensure trusted and auditable data pipelines.Design and support CI/CD-enabled data engineering platforms, automated deployments, and integration with enterprise data ecosystems including Dataiku, Neo4j, REST APIs, and cloud-native services. Collaborate with Data Scientists and ML Engineers to support feature availability, data access, pipeline orchestration, integration testing, and ML operationalization.Strong analytical, problem-solving, and troubleshooting skills; exposure to GenAI use cases and MLOps ecosystems is a plus.PreferredExperienceOverall 10+ years of experience5+ years on GCP Data Engineering5+ years with Python/Dataflow-based ETL development3+ years with Composer/Airflow, BigQuery/PostgreSQL, and Google Cloud StorageExperience supporting fraud detection, risk analytics, or ML data platforms preferred.","company":"United It","rawCompany":"united it","city":"Austin","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-10-06T07:15:07.284Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer, Analytics","description":"Senior GCP Data Engineer (ML & Fraud Analytics Data Platform)Location: Austin TX (100% Onsite)Skills Required: GCP, BigQuery, Python, Dataflow, Composer/Airflow, Google Cloud Storage (GCS)Key Responsibilities & SkillsDesign, develop, and maintain scalable ETL/data pipelines on GCP using Python, Dataflow, BigQuery, Cloud Storage, Composer/Airflow, and Control-M to support fraud analytics, ML, and enterprise data initiatives.Build and optimize ML-ready datasets, feature engineering pipelines, and reusable data assets for model training, validation, and production deployment.Develop high-quality Python solutions following coding standards, security best practices, resiliency, reliability, and performance optimization principles.Strong expertise in SQL, BigQuery/PostgreSQL, data modelling, database concepts, and large-scale data processing.Implement data quality, reconciliation, lineage, metadata management, governance, and monitoring controls to ensure trusted and auditable data pipelines.Design and support CI/CD-enabled data engineering platforms, automated deployments, and integration with enterprise data ecosystems including Dataiku, Neo4j, REST APIs, and cloud-native services. Collaborate with Data Scientists and ML Engineers to support feature availability, data access, pipeline orchestration, integration testing, and ML operationalization.Strong analytical, problem-solving, and troubleshooting skills; exposure to GenAI use cases and MLOps ecosystems is a plus.PreferredExperienceOverall 10+ years of experience5+ years on GCP Data Engineering5+ years with Python/Dataflow-based ETL development3+ years with Composer/Airflow, BigQuery/PostgreSQL, and Google Cloud StorageExperience supporting fraud detection, risk analytics, or ML data platforms preferred.","datePosted":"2026-10-06T07:15:07.284Z","dateModified":"2026-10-06T07:15:07.284Z","hiringOrganization":{"@type":"Organization","name":"United It","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Austin","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"ac7d1897f55611ffcdae9e76"},"url":"https://jobsearcher.com/jobs/ac7d1897f55611ffcdae9e76"}}