
Specializing in fast fashion.
Technical Director (Data Engineering)
About SHEIN
SHEIN is a global online fashion and lifestyle retailer, offering SHEIN branded apparel and products from a global network of vendors, all at affordable prices. Headquartered in Singapore, with more than 15,000 employees operating from offices around the world, SHEIN is committed to making the beauty of fashion accessible to all, promoting its industry-leading, on-demand production methodology, for a smarter, future-ready industry.
Position Summary
We’re seeking a full-time Technical Director for Data Engineering and Intelligence (Official Title: Director I, Data Engineering and Intelligence) for our San Diego-based corporate office, who will lead and oversee our US data engineering, intelligence, and infrastructure teams. This is a technical leadership role where you will drive innovation, mentor engineers, supervise operations, and shape the future of SHEIN’s data ecosystem. Reporting directly to the CTO, you will shape the company’s data technology strategy, architecture, and operations at scale.
Job Responsibilities
Technical Leadership & Innovation
A strong ability to leverage AI to drive large-scale automation and lead AI-driven transformation across data engineering and intelligence practices, with hands-on familiarity with modern AI-native development tools (e.g., Claude Code).
- Prior experience as a data or technology leader (e.g., tech lead or architect) is required. We are looking for someone who not only has deep knowledge of modern data infrastructure, but also brings strong perspectives and ideas—someone who can provide guidance, influence technical direction, and serve as a thought leader to help evolve and strengthen our ecosystem.
People Management
The role is expected to balance approximately 50% leadership and team management with 50% focus on driving technology advancement and providing technical thought leadership.
You will be expected to lead a team of 10–20 engineers, overseeing recruiting, career development, performance management, and team structure for the engineering organization.
Strategic Collaboration
- Partner closely with the CTO to define and execute long-term data technology initiatives, including infrastructure modernization, AI transformation, and operational excellence.
Global Operations & Cross-Regional Collaboration
Lead and optimize U.S.-based data operations while working closely with teams across APAC and global headquarters to align workflows and strengthen global data capabilities. The role requires strong cross-cultural leadership and organizational influence—someone who can build trust across regions, navigate complex organizational structures, and effectively collaborate across cultural and functional boundaries to drive alignment and progress.
Data Infrastructure & Best Practices
- Architect, build, and refine large-scale data pipelines and cloud-based infrastructure solutions, ensuring they meet best practices and regulatory requirements.
Job Requirements
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Master’s degree in Computer Science or a related field.
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5+ years of industry experience in data engineering, data infrastructure, or software development (8+ years preferred).
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2+ years of engineering management experience (3+ years preferred), with a demonstrated ability to lead, mentor, and grow engineering teams.
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Deep expertise in modern cloud platforms and large-scale data infrastructure, including technologies within the Map Reduce ecosystem and distributed data processing frameworks
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Hands-on familiarity with modern AI technologies and AI-native development tools (e.g., Claude Code, MCP, and related tooling).
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Proven ability to operate and improve large-scale technical systems, including diagnosing complex infrastructure and data quality issues and implementing scalable solutions.
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Strong computer science fundamentals, particularly in Linux systems, networking, and SQL.
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Proficiency in scripting and automation, especially using Python and Bash (these skills will be assessed during the interview process).
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Experience working with containerized and distributed systems such as Kubernetes and Docker, as well as designing high-availability architectures.
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At least 3 years of experience collaborating with APAC-based teams or other international engineering organizations.
Nice to Have
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Experience with Azure.
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Experience managing people leaders
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Knowledge of data streaming technologies (e.g., Flink, Hive).
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Prior experience in the e Commerce space.
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Bilingual in Mandarin.
Benefits and Perks
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Bonus and RSU eligible
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Healthcare (medical, dental, vision, prescription drugs)
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Health Savings Account with Employer Funding
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Flexible Spending Accounts (Healthcare and Dependent care)
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Company-Paid Basic Life/AD&D insurance
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Company-Paid Short-Term and Long-Term Disability
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Voluntary Benefit Offerings (Voluntary Life/AD&D, Hospital Indemnity, Critical Illness, and Accident)
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Employee Assistance Program
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Business Travel Accident Insurance
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401(k) Savings Plan with discretionary company match and access to a financial advisor
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Vacation, paid holidays, floating holiday and sick days
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Employee discounts
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Free weekly catered lunch
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Dog-friendly office (available at select locations)
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Free gym access (available at select locations)
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Free swag giveaways
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Annual Holiday Party
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Invitations to pop-ups and other company events
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Complimentary daily office snacks and beverages
Pay Range**$147,600—$265,200 USD**
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SHEINについて

SHEIN
Series F+Shein is a global e-commerce platform specializing in fast fashion. While the company primarily focuses on women's clothing, it also offers men's apparel, children's wear, accessories, cosmetics, shoes, bags, and other fashion items.
10,001+
従業員数
Singapore
本社所在地
$100B
企業価値
レビュー
8件のレビュー
4.3
8件のレビュー
ワークライフバランス
4.2
報酬
4.0
企業文化
4.1
キャリア
3.5
経営陣
3.8
75%
知人への推奨率
良い点
Great work environment and friendly people
Work from home flexibility
Good pay and benefits
改善点
Team layoffs due to overseas hiring
Monotonous daily work
Difficulty during termination periods
給与レンジ
67件のデータ
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Associate Big Data Engineer I
3件のレポート
$126,100
年収総額
基本給
$97,000
ストック
-
ボーナス
-
$123,500
$144,300
面接レビュー
レビュー1件
難易度
3.0
/ 5
期間
14-28週間
面接プロセス
1
Application Review
2
HR Screen
3
Technical Interview
4
Hiring Manager Interview
5
Offer
よくある質問
Technical Knowledge
AI/ML Concepts
Research Experience
Behavioral/STAR
Past Experience
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