Data Engineer

• Lead the design, development, and maintenance of data pipelines and Extract, Transform, and Load/Extract, Load and Transform (ETL/ELT) processes for the centralized data warehouse.
• Architect and optimize SQL queries for data transformation, analytics, and reporting.
• Develop and manage data foundations and models specifically designed to support Artificial Intelligence/Machine Learning (AI/ML) initiatives and the generation of AI-motivated insights. Develop and maintain data infrastructure to support the data foundations.
• Partner with executive business stakeholders, data scientists, and Artificial Intelligence (AI) teams to understand requirements, architect data solutions.
• Collaborate with other data engineers to deliver data solutions and promote technical growth within the team.

Minimum qualifications:

• Bachelor’s degree in Computer Science, Engineering, Information Systems, a related quantitative field, or equivalent practical experience.
• 3 years of experience in a Data Engineering, Data Infrastructure, or Data Analytics role.
• Experience with data engineering and writing software in Python or SQL.
• Experience in managing and maintaining data projects from conception to production.
• Experience building and maintaining data pipelines tailored for ML, AI, or advanced analytics workloads.

Preferred qualifications:

• Experience supporting AI/ML initiatives and with Generative AI technologies, LLM integrations, RAG, Fine-tuning of models and vector databases.
• Experience building and productionizing end-to-end data pipelines using ETL tools.
• Experience with advanced data modeling and schema design for analytics.
• Expertise with Google Cloud Platform (GCP) data services (e.g., BigQuery, Dataflow, Pub/Sub) and AI infrastructure (e.g., Vertex AI, BigQuery ML).
• Familiarity with the consumer electronics industry or supply chain data.
• Excellent stakeholder management and communication skills, with the ability to translate technical concepts to non-technical audiences.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, a related quantitative field, or equivalent practical experience.
• 3 years of experience in a Data Engineering, Data Infrastructure, or Data Analytics role.
• Experience with data engineering and writing software in Python or SQL.
• Experience in managing and maintaining data projects from conception to production.
• Experience building and maintaining data pipelines tailored for ML, AI, or advanced analytics workloads.