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Tier-1 brand, mid-level generalist data role in metro with broad cloud and ETL requirements.
Core cloud data engineering skills transferable across industries; low industry-specific bias.
Explicit 5+ years plus mandatory GCP, Snowflake, PySpark, and ETL/CI/CD requirements.
Design and maintain scalable, reliable data architectures and ETL/ELT pipelines on Google Cloud Platform using Snowflake and BigQuery.
Optimize and tune data processing and warehouse performance including cost management and security implementations.
Lead data migration from on-premises to cloud and integrate diverse data sources ensuring data quality, governance, and monitoring frameworks.
Minimum 5 years of experience implementing data architectures on Google Cloud Platform.
Strong proficiency with Snowflake, BigQuery, Python, SQL, and PySpark.
Experience building batch and real-time data pipelines using GCP services such as Dataproc, Cloud Functions, Pub/Sub, and Cloud Composer.
Work Experience Required: At least 5 years in relevant data engineering roles.
Experienced in cloud-native data warehouse design, especially with Snowflake and GCP ecosystem integration.
Capable of translating business requirements into scalable technical data solutions with an emphasis on performance and cost optimization.
Skilled at cross-functional collaboration with Data Science, Analysis, and Business teams to deliver production-grade data platforms.