1. Data Pipeline Development
Assist in building and maintaining data ingestion and transformation pipelines
Support ETL / ELT processes from multiple data sources
Monitor pipeline jobs and help troubleshoot data issues
2. Data Platform & Storage
Support development on data platforms such as: Data warehouses / data lakes
Assist with table design, schema changes, and performance optimization
Ensure data consistency and reliability
3. Cloud & Tooling Support
Work with cloud data platforms (Azure / AWS - training provided)
Support CI/CD, scheduling, and automation for data workflows
Follow coding standards and best practices
4. Collaboration
Work closely with Data Engineering and
Data Analysts (to support reporting and dashboards)
Participate in requirement discussions and technical reviews
Document data pipelines and technical workflows
5. Learning & Growth
Learn modern data engineering tools and architectures
Gradually take ownership of small-to-medium data pipelines
Follow guidance from Senior Data Engineers and Tech Leads
1. Experience
1 - 2 years of experience in Data Engineering or related roles
Fresh graduates with strong academic projects or internships are welcome
2. Technical Foundation
A solid technical foundation is essential for success in data engineering roles. Candidates should demonstrate the following core competencies:
Basic Knowledge
SQL: Familiarity with writing queries, performing joins, and understanding basic optimization techniques.
Relational databases: Understanding how relational databases function and their role in data management.
Core Concepts
ETL / data pipelines: Knowledge of Extract, Transform, Load processes and the architecture of data pipelines.
Data warehousing fundamentals: Awareness of data warehousing principles and their importance in storing and organizing large datasets.
Programming Skills
Basic programming knowledge: Experience with Python or similar programming languages to support data engineering tasks.
Nice to Have
Exposure to Cloud platforms (Azure / AWS) and Data tools (Airflow, dbt, Spark, etc.)
Basic understanding of analytics or AI data requirements
3. Soft Skills
Logical thinking and problem-solving mindset
Willingness to learn and adapt to new technologies
Ability to work well in a team environment
Attention to detail and responsibility for data quality
4. Education
Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related fields
1. Career path development
Learning & Career Development from Data Engineer (
Fresher / Junior) → Data Engineer → Senior Data Engineer → Data Architect / Platform Lead
Hands-on experience with enterprise-scale data platforms
Clear technical growth path with mentoring
Training and support for professional certifications
2. Compensation & Benefits
Competitive salary and performance bonus
13th-month salary
Health insurance, paid leave, and other benefits
Annual performance review
3. Work Environment
Flexible working policy
Working hours: Monday - Friday, 9:00 AM - 6:00 PM
Team building, company trips, and knowledge-sharing sessions
Why Join Datatyk
Work on real enterprise analytics & AI projects
Clear career growth toward Analytics Consultant / AI Analytics Lead
Exposure to multiple industries and modern data platforms
Competitive compensation and flexible working environment
Work location: 46 Bạch Đằng, Phường Tân Sơn Hòa, Thành phố Hồ Chí Minh