Job description

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, SHEIN remains committed to making the beauty of fashion accessible to all, promoting its industry-leading, on-demand production methodology for a smarter, future-ready industry. Founded in 2012, SHEIN has more than 16,000 employees operating from offices around the world and continues to expand operations globally. Join SHEIN and be the future! Position Summary SHEIN Technology is seeking a full-time Senior Data Engineer I (Intelligent Automation) embedded within the Data Engineering team, reporting to Director, Data Engineering. This role applies GenAI/LLM capabilities to real data-engineering workflows, turning prototypes into reliable internal tools that improve engineering productivity, operational efficiency, and data access. The primary focus is AI automation for Data Engineering—not requiring deep expertise across every data-platform technology on day one. The ideal candidate combines hands-on GenAI engineering, strong Python/SQL and software fundamentals, and practical production ownership. Job Responsibilities Build and productionize GenAI/LLM solutions for BDE workflows, including code/SQL assistance, metadata and lineage discovery, data retrieval, and engineering knowledge access. Develop retrieval/RAG and agentic workflows that connect engineering documentation, SOPs, databases, metadata, logs, APIs, and internal platforms using appropriate evaluation, guardrails, and access controls. Improve BDE operational efficiency through AI-assisted incident triage, log/alert analysis, root-cause analysis, and repeatable workflow automation. Integrate AI capabilities into reusable internal services and developer tools; establish monitoring, feedback loops, quality metrics, and adoption measures to move solutions from prototype to sustained production use. Partner with Data Engineering, AI, SRE, Database, Platform, and global teams to identify high-value use cases and integrate solutions into existing data workflows. Own scoped projects independently from problem definition through implementation and production support, and contribute to practical engineering standards and documentation. Job Requirements Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent technical discipline. 3+ years of software, machine learning, data, or platform engineering experience, including hands-on ownership of production systems, services, or developer-facing tools. Strong Python and SQL skills, solid software-engineering fundamentals, and practical understanding of databases, APIs, data pipelines, and distributed systems. Hands-on experience building GenAI/LLM applications using one or more of RAG/retrieval, embeddings, tool/function calling, agents, prompt workflows, or model APIs. Experience productionizing services, automation, or data/ML workloads with testing, CI/CD, monitoring, logging, security considerations, and incident troubleshooting. Strong ownership and communication skills, with the ability to translate ambiguous engineering pain points into focused, measurable solutions and work effectively with geographically distributed teams. Nice to Have Experience with Spark, Flink, Kafka, Hive/lakehouse systems, Airflow, Kubernetes, or similar large-scale data technologies. Experience with metadata/lineage, enterprise search or knowledge systems, developer productivity, data retrieval, observability, or incident/RCA automation. Familiarity with cloud-scale data platforms and modern table formats such as Paimon, Iceberg, or Delta Lake. Experience driving adoption of internal AI tools or working in high-scale e-commerce or data-platform environments. Benefits and Perks Bonus eligible Healthcare (medical, dental, vision, prescription drugs) Health Savings Account with Employer Funding Flexible Spending Accounts (Healthcare and Dependent care) Company-Paid Basic Life/AD&D insurance Company-Paid Short-Term and Long-Term Disability Voluntary Benefit Offerings (Voluntary Life/AD&D, Hospital Indemnity, Critical Illness, and Accident) Employee Assistance Program Business Travel Accident Insurance 401(k) Savings Plan with discretionary company match and access to a financial advisor Vacation, paid holidays, floating holiday and sick days Employee discounts Free weekly catered lunch Dog-friendly office (available at select locations) Free gym access (available at select locations) Free swag giveaways Annual Holiday Party Invitations to pop-ups and other company events Complimentary daily office snacks and beverages #LI-ED1 Pay Range $122,600 — $177,900 USD

Requirements

Must-haves

Build and productionize GenAI/LLM solutions for BDE workflows, including code/SQL assistance, metadata and lineage discovery, data retrieval, and engineering knowledge access.
Develop retrieval/RAG and agentic workflows that connect engineering documentation, SOPs, databases, metadata, logs, APIs, and internal platforms using appropriate evaluation, guardrails, and access controls.
Improve BDE operational efficiency through AI-assisted incident triage, log/alert analysis, root-cause analysis, and repeatable workflow automation.
Integrate AI capabilities into reusable internal services and developer tools; establish monitoring, feedback loops, quality metrics, and adoption measures to move solutions from prototype to sustained production use.
Partner with Data Engineering, AI, SRE, Database, Platform, and global teams to identify high-value use cases and integrate solutions into existing data workflows.
Own scoped projects independently from problem definition through implementation and production support, and contribute to practical engineering standards and documentation.
Job Requirements
Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent technical discipline.
3+ years of software, machine learning, data, or platform engineering experience, including hands-on ownership of production systems, services, or developer-facing tools.
Strong Python and SQL skills, solid software-engineering fundamentals, and practical understanding of databases, APIs, data pipelines, and distributed systems.
Hands-on experience building GenAI/LLM applications using one or more of RAG/retrieval, embeddings, tool/function calling, agents, prompt workflows, or model APIs.
Experience productionizing services, automation, or data/ML workloads with testing, CI/CD, monitoring, logging, security considerations, and incident troubleshooting.
Strong ownership and communication skills, with the ability to translate ambiguous engineering pain points into focused, measurable solutions and work effectively with geographically distributed teams.

Nice-to-haves

Experience with Spark, Flink, Kafka, Hive/lakehouse systems, Airflow, Kubernetes, or similar large-scale data technologies.
Experience with metadata/lineage, enterprise search or knowledge systems, developer productivity, data retrieval, observability, or incident/RCA automation.
Familiarity with cloud-scale data platforms and modern table formats such as Paimon, Iceberg, or Delta Lake.
Experience driving adoption of internal AI tools or working in high-scale e-commerce or data-platform environments.

Application prep

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Keywords to mirror

llmaipythonsqlmachine learningmlci/cdkubernetes

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)