Lead data engineer Google Cloud Platform (only w2/1099)

A lead data engineer on Google Cloud Platform (Google Cloud Platform) for financial services should design, enable, and secure a modern data lake that supports advanced AI/ML workloads and regulatory reporting. This role requires expertise in scalable architecture, deep data governance, and the ability to operationalize data for analytics and compliance.

Key Responsibilities:

• Architect and build high-performance, compliant data pipeline frameworks that support batch, streaming, and real-time use cases on a well-governed financial data lake using Google Cloud Platform services such as Cloud Storage, BigQuery, Dataplex, and Data Catalog.
• Define and maintain data modeling and metadata standards to ensure traceability and auditability.
• Implement data lineage, cataloging, and observability frameworks aligned with financial data governance mandates.
• Build robust ETL/ELT pipelines in BigQuery, Dataflow, and Dataproc, with orchestration through Airflow or Cloud Composer.
• Enable real-time analytics and event-driven data integration using Pub/Sub, Kafka, or similar technologies.
• Implement data quality validation and anomaly detection frameworks.
• Develop and optimize BigQuery schemas, partitioning, and clustering strategies to manage large-scale financial datalakes and warehouses.
• Implement automated data lineage and auditability for regulatory transparency with services like Dataplex and Data Fusion Lineage.
• Operationalize AI/ML by supporting real-time and batch data pipelines, leveraging BigQuery ML, Dataflow, and Vertex AI for advanced analytics, risk scoring,