Senior Data Engineer

Top 3 reasons to join us

• User-first mindset, solving real needs with impact
• Data-driven culture, decisions backed by insights
• Safe space to innovate, fail fast and grow faster

Job description

About GHN

Giao Hàng Nhanh (GHN) is one of Vietnam’s leading logistics companies, proudly delivering exceptional services with the commitment: “Smarter, Faster, More Cost-Effective.” GHN empowers millions of businesses to optimize their operations while creating thousands of jobs for the Vietnamese workforce.

Founded with the mission to revolutionize the logistics industry and guided by a technology-driven vision, GHN continuously integrates advanced technological solutions into every delivery. This enables streamlined operations, enhanced delivery performance, and a fast, safe, and efficient customer experience - serving a wide range of clients including E-commerce platforms, retailers, and individual consumers.

With a nationwide network spanning all 63 provinces and cities, a forward-thinking innovation strategy, and robust logistics infrastructure, GHN continues to affirm its position as a pioneer in Vietnam’s rapidly growing E-commerce and logistics sector."

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 AI & Data Team

At GHN, our highly motivated AI & Data team 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 2 (S4) to join our dynamic AI & Data team. This pivotal role will be responsible for expanding and optimizing our big data collections and flows, designing scalable data pipeline architectures, and ensuring the robust integration of data for AI/ML-powered applications. The ideal candidate is an expert in big data engineering who thrives on optimizing complex data systems and building foundational infrastructure from the ground up to develop, deliver, and strengthen our AI & Data Platform. This platform is crucial for enabling all GHN’s users - employees, drivers, and customers - through advanced and robust data-driven insights and solutions. The Senior Data Engineer 2 will provide technical expertise, mentor junior team members, and collaborate closely with Data Scientists, ML Engineers, and other cross-functional teams to ensure optimal data delivery architecture and quality for ongoing AI/ML initiatives.

Key Responsibilities

• Big Data Platform Design & Optimization:
  • Design, build, and maintain optimal big data pipeline architectures that are crucial for GHN's AI/ML solutions, ensuring high availability, scalability, and efficiency.
  • Develop robust ETL/ELT solutions for optimal extraction, transformation, and loading of high-quality data from a wide variety of internal and external data sources (e.g., MongoDB, Postgres, e-commerce sites, social platforms).
  • Optimize data writing and reading performance across various database systems and data lakes to support real-time and batch processing requirements.
  • Make technical choices and build systems and tools to manage the entire data lifecycle of large, complex datasets.
• AI/ML Data Application Integration & Development:
  • Collaborate closely with Data Scientists and ML Engineers to design and implement data solutions that support the development, training, and deployment of AI/ML models (e.g., demand forecasting, logistics optimization, fraud detection, customer segmentation).
  • Oversee and contribute to the integration of AI/ML models into the broader product infrastructure and user experience, ensuring seamless deployment and operation.
  • Develop and implement data pipelines specifically for AI/ML model data preparation, including feature engineering, data enrichment, backfilling, merging, deduplicating, and ensuring data compatibility and format for various model inputs.
• Data Quality, Governance & Monitoring:
  • Implement and monitor robust data quality frameworks to ensure data accuracy, consistency, and integrity across all data sources, identifying and resolving potential issues proactively.
  • Design and apply data governance solutions (e.g., using Apache Ranger) to manage data access, privacy, and compliance for large-scale projects, including ensuring legal and regulatory adherence.
  • Build and customize metrics for monitoring and alerting tools to support incident detection and ensure the consistency and reliability of data services and pipelines.
• Technical Expertise & Collaboration:
  • Provide technical guidance and mentorship to junior data engineers, fostering their professional development and promoting best practices in data engineering and AI/ML data readiness.
  • Work closely with cross-functional teams including Data Analysts, Data Scientists, Product Managers, to understand business requirements and translate them into robust, data-driven solutions.
  • Identify, design, and implement internal process enhancements through automation, optimizing data delivery and infrastructure for greater scalability and efficiency.
  • Stay current on published state-of-the-art big data technologies and AI/ML data engineering techniques for continuous platform improvement.

Your skills and experience

• Experience:
  • 4+ years of progressive experience in Data Engineer or Software Engineer roles, with a strong focus on big data engineering.
  • Proven experience in designing, building, and optimizing big data pipelines, architectures, and datasets.
  • Demonstrated experience in integrating data for AI/ML-powered applications, including working with Data Scientists or ML Engineers on model data preparation, feature engineering, and deployment.
  • Experience in leading technical aspects of data engineering projects or initiatives within complex organizational structures.
• Skills:
  • Expert proficiency in programming languages such as Python, Java, or Scala.
  • Deep expertise in big data technologies like Hadoop, Trino, Doris, Spark, Kafka, Kafka Connect (Debezium, Confluent, etc), Airflow, Superset, DBT, Iceberg, or similar.
  • Strong proficiency in SQL and NoSQL query languages (e.g., MySQL, MongoDB, PostgresDB, Elasticsearch) for complex data manipulation and extraction.
  • Hands-on experience with cloud services (e.g., Google Cloud Storage, Google BigQuery, CloudSQL, Dataproc, Kubernetes Engine, Vertex AI,...).
  • Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes, ArgoCD).
  • Familiarity with machine learning concepts, feature engineering, and data preparation techniques for model training.
  • Excellent problem-solving, analytical, and critical thinking skills, with a strong attention to detail.
  • Strong communication (verbal, written, visual) and interpersonal skills to convey complex technical information to diverse audiences and facilitate collaboration.
  • Ability to work effectively in a fast-paced, dynamic environment and manage multiple tasks and deadlines.
• 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.

Why you'll love working here

• 13th-month salary, performance bonuses, and KPI bonuses
• Health insurance, Social insurance, and Unemployment insurance
• Medical insurance
• Annual health checkup
• Annual salary reviews
• Annual team building/company trip
• Ongoing internal and external training opportunities.