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Data Engineer

Summary

Design and maintain data pipelines and models that power research and industry analysis for a semiconductor and AI-focused research firm.

Employment Type: Full-Time

Work Setting: In-office

Work Location: Singapore

Work Hours: Office hours

Find out more here:

About SemiAnalysis

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 40 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 data models 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.
  • If you have a favorite SCD type (mine's Type 2), we should probably talk.

Responsibilities

  • Work with lead analysts to ensure data accuracy, completeness, and utility value across multiple sources and formats.
  • 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.
  • Open-minded and resourceful with technical solutions and functionality of platforms.
  • Maintain strong relationships with lead analysts and stakeholders to build solutions of the right fit.

Requirements

  • At least 3 years of experience in a Data Engineering, Data Science or reasonably equivalent role.
  • Capable in Python, SQL, and Excel.
  • Strong ETL development experience.
  • 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.

Growth Areas

  • Develop a deep understanding of data modelling in real-world industry contexts, not just pipelines, but how data drives decision-making and research narratives
  • Gain exposure to cutting-edge domains including AI infrastructure, semiconductors, and datacenters
  • Work closely with experienced analysts to bridge the gap between raw data and high-impact insights
  • Take ownership of systems end-to-end, growing into someone who can design, scale, and maintain production-grade data architecture
  • Build strong judgment on trade-offs between speed, accuracy, and scalability in a fast-moving research environment

See also