Job Descriptions
- Participate in building and optimizing data pipelines for clients in on-premises environments: collecting, processing, cleaning, transforming, and supporting data visualization based on project requirements.
- Assist in setting up infrastructure to support ETL/ELT processes from multiple data sources using SQL and common Big Data technologies.
- Support the setup and operation of on-premises components such as Apache Spark, Kafka, Hadoop, NiFi, MinIO, Docker/K8S, Trino, Iceberg, depending on the project.
- Contribute to optimizing pipeline performance, automating manual workflows, improving data transfer efficiency, and enhancing system scalability.
- Work directly with clients to understand requirements and propose appropriate solutions for on-premises data systems.
- Collaborate with Data Analysts, Data Scientists, and DevOps engineers to improve system stability, reliability, and performance.
- Participate in writing technical documentation, deployment processes, and supporting data testing.
Requirements
- Bachelor's degree in Computer Science, Information Technology, Software Engineering, or a related field.
Junior Level
- 1 2.5 years of experience as a Data Engineer or Backend Engineer with data-related tasks.
- Solid programming foundation and proficiency in at least one language: Python / Java / Scala.
- Understanding of SQL and relational databases (MySQL, PostgreSQL, or similar), plus basic knowledge of distributed/big data systems.
- Familiarity with Linux and Git.
- Ability to read and understand technical documentation in English.
Middle Level
- At least 2.5 4 years of experience as a Data Engineer, preferably with on-premises deployment experience.
- Strong SQL skills and experience working with RDBMS (especially Oracle), plus hands-on experience with Kafka / Spark / Hadoop / Airflow or similar tools.
- Proficiency in Python/Java/Scala with solid understanding of file processing, logging, performance optimization, and data testing.
- Experience with documentation writing, data validation, and pipeline optimization.
- Good understanding of data modeling and data architecture.
- Experience with Data Warehouse / Data Lakehouse on-premises projects is a strong advantage.
Benefits
- Competitive and negotiable compensation package, including additional project bonuses.
- 13th-month salary and annual performance review
- Holiday bonuses for four major occasions: April 30, September 2, Lunar New Year, and New Year
- Company trip, quarterly/monthly team building activities, and internal cultural events
- Social and health insurance in compliance with Vietnamese law
- BSH health insurance package covering medical expenses
- Annual health check-up
- Union benefits: Birthday gifts, special occasion allowances, etc.
- Dynamic and open technical environment encouraging knowledge sharing, internal seminars, and sustainable career development
- Opportunity to work on large-scale projects using cutting-edge technologies
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