Data Engineer

4 days ago

Singapur, Singapore SemiAnalysis Full time

SemiAnalysis is an independent research and analysis firm specializing in the Semiconductor and AI industries. Our in-depth coverage spans the entire supply chain, from semiconductor fabrication processes to cutting-edge AI models, software, and infrastructure. We are recognized as the leading authority on the semiconductor supply chain, with the highest concentration of industry experts within one team, and a deep-rooted passion for delving into the intricacies. We’re a global team of over 20 analysts, each with extensive networks across the semiconductor supply chain and AI ecosystem, publishing industry-shaping articles while participating in 40+ conferences annually. Our newsletter reaches more than 200,000 subscribers worldwide, including senior management and C-suite leaders at the leading semiconductor and AI companies. We also offer three core products: Industry Models – We develop and publish models on accelerator shipments, datacenter demand and supply, GPU total cost of ownership, and more. Core Research – We distill deep technical research into key insights on technology and product trends. Consulting and Technical Due Diligence – We conduct custom research and project work for the largest funds, leading venture-capital firms, companies across the AI ecosystem, and government agencies. Position Overview We are seeking a clever and motivated Data Engineer to join our team in Singapore. You’ll be the architect and maintainer of the pipelines, data models, and infrastructure that power our industry models, research, and consulting work. This role requires a mix of technical expertise, autonomy, and pragmatism—you’ll need to work independently, collaborate across our globally distributed team, and build systems that are both accurate, robust, observable, and modular. Key Responsibilities Design, develop, and maintain robust and scalable ETL pipelines in Python to power our industry models and analytics products. Work with lead analysts to ensure data accuracy, completeness, and utility value across multiple sources and formats. Build scalable and reusable data workflows in cloud environments (GCP, AWS, or Azure). Implement and maintain data quality monitoring. Able to effectively use a SQL database via automated cron jobs. Maintain and extend dashboards and APIs that deliver data to both internal analysts and external clients. Support the integration of new datasets, tools, and infrastructure components to enhance our analytics capabilities. Qualifications – Must Haves 1–3 years of experience in a Data Engineering, Data Science or reasonably equivalent role. Capable in Python , SQL , and Excel . Hands-on experience with at least one cloud platform (GCP , AWS , or Azure ). Highly autonomous—able to take a problem from definition to deployment with minimal oversight. The right combination of opinionated and low-drama. Plusses (Nice to Have) Experience with Flask , Redis , Dash , Airflow , GitHub Actions , and/or Kubernetes . Familiarity with automated regression, smoke, or unit testing methodologies. Experience working with messy, real-world data. Location Full-time role based in Singapore #J-18808-Ljbffr

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