(Senior) Data Engineer

About GHN

Giao Hang Nhanh (GHN) is one of Vietnam's leading logistics enterprises, confidently providing superior services: SMARTER, FASTER, MORE COST-EFFECTIVE. We support millions of businesses in optimizing their operations and create thousands of jobs for the Vietnamese people.

Established with the mission to revolutionize the logistics industry and driven by a technology-centric development approach, GHN continuously applies advanced technological solutions to every order. This aims to streamline operational processes, enhance delivery efficiency, and provide fast, secure, and effective service experiences for all customer segments – from e-commerce platforms and retailers to individual consumers.

With a nationwide network covering all 34 provinces and a strategy of continuous innovation alongside a robust infrastructure system, GHN has been affirming its pioneering position in the rapidly growing e-commerce and logistics sectors in Vietnam.

Why Join GHN

This is a pivotal opportunity to join a rapidly growing e-commerce delivery leader in Vietnam, where your contributions will directly impact our strategic direction and market position. You will be part of a team that embraces cutting-edge technologies, data- driven innovation & discruption to solve real-world problems and enhance millions of lives. We offer a dynamic and collaborative environment where you can leverage your expertise, grow professionally through challenging projects, and make a significant impact on our success.

About the Core AI & Data Platform Department

At GHN, our highly motivated Core AI & Data Platform Department is dedicated to establishing GHN as the fastest, most reliable, and convenient delivery service in Vietnam. We achieve this by developing and adopting advanced, data-driven decisions and solutions, making data capability a core business driver for operational efficiency, scalability, and customer trust and happiness.

Job Summary

We are seeking a highly skilled and experienced Senior Data Engineer to design, build, and scale our modern data platform and infrastructure. This role is critical to ensuring the reliability, performance, and security of our end-to-end data ecosystem, supporting both operational and analytical workloads across the organization.

The ideal candidate combines strong data engineering expertise with deep knowledge of distributed systems, cloud infrastructure, and DevOps practices. You will be responsible for developing scalable data pipelines, optimizing real-time and batch processing systems, automating platform operations, and driving best practices for data reliability and observability.

You will work closely with software engineers, platform teams, analysts, and product stakeholders to enable data-driven decision-making and deliver resilient, high-performance data solutions built primarily on open-source technologies.

Key Responsibilities

• Design & Build Data Pipeline: Architect scalable batch and real-time data pipelines, build and maintain ETL/ELT workflows. Design data lakes, warehouses, and lakehouse architectures. Optimize storage, partitioning, indexing, and query performance.
• Data Modeling & Architecture: Create logical and physical data models. Define data standards and governance practices. Ensure data quality, consistency, lineage, and reliability. Support analytics, BI, AI/ML, and operational systems.
• Database & Query Optimization: Tune queries and optimize pipeline execution. Implement replication, partitioning, and backup strategies. Strong understanding of SQL, able to query and manipulate required data from SQL data sources well.
• Security & Governance: Implement access control and encryption. Ensure compliance with data regulations. Build auditing and observability mechanisms.

Our Comprehensive Data Platform Stack

Candidates should have demonstrable, deep experience across the majority of the following technologies:

• Compute & Query: Trino (or Presto), Apache Spark, Google BigQuery, Apache Doris
• Streaming & Messaging: Apache Flink, Apache Kafka, RabbitMQ
• CDC & Connectors: Kafka Connect (e.g., Debezium, Confluent)
• Infrastructure & Orchestration: Google Kubernetes Engine (GKE), Apache Airflow
• Databases: MongoDB, AlloyDB, MySQL, Redis
• Policy & Security: Apache Ranger, Google Secret Manager, KMS
• CI/CD & Tooling: GitLab, ArgoCD
• Languages: Python, Java, Scala, Go
• Storage & Metadata: GCS, Hive Metastore, DataHub
• Table Format: Apache Iceberg
• Observability: Grafana, Superset, Metabase, Looker

Qualifications

• Experience: 3+ years in a Data Engineer role with a proven track record of designing, building, and maintaining scalable data pipelines.
• Cloud Native: Deep expertise in cloud-native architecture, particularly on Google Cloud Platform (GCP). Familiarity with BigQuery for processing and analyzing large datasets.
• Automation & Scripting: Proficiency in Python/Java/Scala for supporting data services is a strong asset.
• Containers & Orchestration: Advanced hands-on experience with Docker and Kubernetes (GKE), including writing custom operators or complex deployment manifests.
• Communication: Excellent communication skills, capable of explaining complex technical issues to both technical and non-technical stakeholders.

Education:

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related quantitative technical field.
• Master's degree in a related technical field is highly preferred.

Benefits:

• 13th-month salary and Performance Bonus
• Quarterly KPI bonus
• Social and Unemployment Insurance
• Premium Healthcare Insurance
• Annual health checkup
• Annual salary review
• Annual team building/company trip
• Internal and external training opportunities
• Monthly Happy Hour