A. Job Responsibilities:
- Lead the team to improve scalability, reliability, and cost-efficiency of the Data Platform.
- Design, build, and deploy data pipelines (batch & streaming) using Spark orchestrated via Airflow.
- Develop libraries and frameworks for data ingestion, transformation, and governance with clean architecture principles.
- Collaborate with Data Architects to design/review data models, enforce data contracts, and maintain schema governance.
- Optimize performance with partitioning, caching, Z-Ordering, and metadata management in lakehouse environments (Delta/Iceberg/Hudi).
- Ensure security and compliance: IAM, encryption, secrets management, and GDPR/CCPA adherence.
- Drive CI/CD for data workflows, IaC (Terraform), and container orchestration (Kubernetes).
- Monitor SLOs/SLAs, implement alerting, and lead incident responses and postmortems.
- Design and operate end-to-end ML/LLM pipelines: data prep, training, evaluation, and deployment.
- Build RAG architectures, vector search, and embedding pipelines for LLM-based applications.
B. Job Requirements:
1. Must have:
- Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, or a related technical field
- English is required
- Have 2+ years of experience as a Data Engineer or Software Engineer
- Have experience in Cloud (AWS/Azure/GCP)
- Extremely proficient in at least 1 programming language (Python/Scala/Java)
- Strong experience in systems architecture particularly in complex, scalable, and fault-tolerant distributed systems
- Good at multi-threading, atomic operations, computation framework: Spark (DataFrame, SQL, ...), distributed storage, distributed computing
- Understand designs of resilience, fault-tolerance, high availability, and high scalability, ...
- Tools: CI/CD, Gitlab, ...
- Good at communication & team working
- Being open-minded, willing to learn new things
2. Nice to have:
- Experience with Databricks (Delta Lake, Unity Catalog, Delta Live Tables) or similar lakehouse technologies is a strong plus.
- Proven ability in performance tuning and optimization for Big Data workloads (Spark/Flink, partitioning, shuffle strategies, caching).
- Familiarity with modern data transformation frameworks (dbt).
- Knowledgeable in AI and LLM technologies is a plus, including prompt engineering, embeddings, and retrieval-augmented generation (RAG).
- Hands-on experience with vector databases (ChromaDB, Vector Search) and LLMOps practices.
C. Working location:
- 06 Quang Trung, Cua Nam ward or 119 Tran Duy Hung, Trung Hoa ward
- 23 Le Duan, HCM
D. Hiring process: Homework => Technical interview => Offer => Onboard
