AI Data Engineer

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

Have 5+ 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