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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, optimize, and maintain scalable data pipelines and ETL/ELT processes for a centralized data warehouse on Google Cloud Platform.
Architect and evolve data foundations and models to support AI/ML initiatives and generate AI-driven insights.
Collaborate with executive stakeholders, data scientists, AI teams, and peers to translate requirements into data solutions and drive data quality and AI-readiness standards.
Minimum Requirements
Bachelor’s degree in Computer Science, Engineering, Information Systems, a related quantitative field, or equivalent practical experience.
Minimum 3 years of experience in Data Engineering, Data Infrastructure, or Data Analytics roles.
Proficiency in Python and SQL for data engineering tasks, with experience managing end-to-end data projects.
Experience building and maintaining data pipelines specifically tailored for ML, AI, or advanced analytics workloads.
Ideal Candidate Profile
Experienced in architecting and productionizing data solutions on Google Cloud Platform, especially BigQuery, Dataflow, Pub/Sub, and AI infrastructure like Vertex AI or BigQuery ML.
Demonstrated ability to collaborate with business and AI stakeholders to deliver solutions that enhance decision-making and product strategy in complex environments.
Proven skills in data modeling, schema design, and supporting advanced analytics and AI/ML initiatives, ideally with exposure to ETL tools and consumer electronics or supply chain data.