Senior Data Engineer I
San Diego · USD 122,600-177,900 / year · 3+ years experience · Full-time · Hybrid · Posted Oct 19, 2026
At a glance
- Experience
- 3+ years experience
- Employment
- Full-time
- Workplace
- Hybrid
- Location
- San Diego
- Salary
- USD 122,600-177,900 / year
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.
About the role
- SHEIN Technology is seeking a full-time Senior Data Engineer I (Intelligent Automation) embedded within the Data Engineering team.
- 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.
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.
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.
Preferred qualifications
- 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
- 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
Skills
- Python
- SQL
- GenAI
- LLM
- RAG
- Spark
- Flink
- Kafka
- Hive
- Airflow
- Kubernetes
- Paimon
Show all 14 skills
- Iceberg
- Delta Lake
