Senior Data Engineer

Shein
San Diego, CA
On-site

Who this role is best for

Best suited to data engineers with GenAI/LLM experience working in high-scale e-commerce environments.

Best fit for

  • Candidates with production ownership experience and AI integration skills in e-commerce or data-platform environments
    — “experience driving adoption of internal AI tools or working in high-scale e-commerce or data-platform environments
  • Individuals who can independently manage projects from definition to production support
    — “Own scoped projects independently from problem definition through implementation and production support
  • Professionals with strong Python/SQL skills and experience in distributed systems and data pipelines
    — “Strong Python and SQL skills, solid software-engineering fundamentals, and practical understanding of databases, APIs, data pipelines, and distributed systems

Things to consider

  • The role requires ownership of production systems and tools, not just development
    — “practical production ownership
  • Collaboration with global teams is a key requirement, which may involve cross-timezone coordination
    — “work effectively with geographically distributed teams

How to stand out

  • Highlight projects where you integrated AI into production workflows or tools
    — “Integrate AI capabilities into reusable internal services and developer tools
  • Showcase experience with AI-assisted automation in incident triage or data retrieval
    — “Improve BDE operational efficiency through AI-assisted incident triage, log/alert analysis, root-cause analysis, and repeatable workflow automation
  • Demonstrate ability to translate ambiguous engineering problems into measurable solutions
    — “ability to translate ambiguous engineering pain points into focused, measurable solutions
  • Emphasize experience with RAG, embeddings, or agents in GenAI/LLM application development
    — “hands-on experience building GenAI/LLM applications using one or more of RAG/retrieval, embeddings, tool/function calling, agents, prompt workflows, or model APIs
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • build and productionize GenAI/LLM solutions for data engineering workflows
  • improve operational efficiency through AI-assisted incident triage
  • integrate AI capabilities into internal services
Typical background
3+ years of software, machine learning, or data engineering experiencehands-on experience with GenAI/LLM applications

Skills & requirements

Required

Genai/llm ApplicationPython/sqlData PipelineDistributed SystemsProduction OwnershipSoftware Engineering FundamentalsAI Integration

Preferred

Large-scale Data TechnologiesCloud Platforms

Stack & domain

PythonSQL

About the role

Original posting from Shein via Greenhouse

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

Source: Shein careers (Greenhouse)

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