Techcombank

Tóm tắt công việc

• 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.

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 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.