Designs and implements scalable, secure, and cost-effective data solutions on the Google Cloud Platform.
Translate complex business requirements into cloud-native data warehouses, data lakes, and streaming pipelines, while ensuring strict data governance, platform modernization, and optimization for AI/ML workloads.
Core Responsibilities
· Platform Architecture: Design and build end-to-end cloud-native data platforms (Data Lakes, Data Warehouses).
· Data Pipelines: Architect and optimize robust ETL/ELT pipelines for batch and real-time processing.
· Cloud Migration: Lead the transition and modernization of legacy on-premises data systems (e.g., Teradata, Oracle, Informatica) to Google Cloud Platform.
· Data Modeling: Translate business needs into logical, conceptual, and physical data models (e.g., star/snowflake schemas, Data Mesh concepts).
· Governance & Security: Implement enterprise-grade security frameworks, data masking, and metadata management.
Required Skills & Qualifications
· Google Cloud Platform Core Services: Deep, production-level expertise in BigQuery, Cloud Storage, Dataflow, Data Fusion, Dataproc, and Pub/Sub.
· Programming Languages: Proficiency in Python and SQL.
· DevOps & Orchestration: Experience with Infrastructure-as-Code (Terraform) and workflow orchestration (Cloud Composer/Apache Airflow).
· Experience Level: Typically requires 15+ years of experience in data engineering or architecture, with at least 3–5 years focused specifically on Google Cloud Platform environments
Never miss an opportunity! Create an alert based on the job you applied for.