A Platform Engineer is responsible for the development of platforms that support the needs and use cases of different engineering teams across the organization. Creates reusable tools and workflows to streamline operational needs and facilitate automation tasks, supporting scalability of DevOps practices.
Senior Google Cloud Platform Data Engineer (ML & Fraud Analytics Data Platform)
Location:
Austin TX (100% Onsite)
Experience:
10+
Years Cloud Platform:
Google Cloud Platform Skills Required:
Google Cloud Platform, BigQuery, Python, Dataflow, Composer/Airflow, Google Cloud Storage (GCS) Key Responsibilities & Skills Design, develop, and maintain scalable ETL/data pipelines on Google Cloud Platform 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. Preferred Experience Overall 10+ years of experience 5+ years on Google Cloud Platform Data Engineering 5+ years with Python/Dataflow-based ETL development 3+ years with Composer/Airflow, BigQuery/PostgreSQL, and Google Cloud Storage Experience supporting fraud detection, risk analytics, or ML data platforms preferred.
