Cross- Company Data Infrastructure Development:
Design, develop, and manage data infrastructure that spans across the organization.
Data Integration and Pipeline Management:
Develop and maintain robust data integration workflows and data pipelines to ensure seamless data movement.
Data Aggregation:
Collect and aggregate data from multiple sources, including internal products, services, and CRM tools, into a centralized data lake.
Data Distribution:
Ensure efficient and secure distribution of data from the data lake to analysis platforms and machine learning systems.
Data Analysis Infrastructure:
Build and maintain infrastructure to support data analysis and enable accurate and timely insights.
Data Warehouse (DWH) Optimization:
Continuously monitor and optimize the performance of the data warehouse (DWH) for scalability and efficiency.
Data Quality Assurance:
Establish and enforce standards and practices to ensure high data quality across all stages of the data lifecycle.
Job Requirements
Majored in Mathematics, Computer Science, or a related field.
Graduated from a top- tier university/college in Vietnam.
AI Software Development:
Hands- on experience in developing AI algorithms or a strong understanding of how they work from scratch.
Skilled in operating and managing API services with appropriate software.
Proficient in building Application Programming Interfaces (APIs) as internet services.
Measured performance using metrics software.
Controlled and fine- tuned accuracy through data operation.
Data Engineering:
Proficient in Python and SQL (BigQuery experience is preferable).
Experience in development and operations using AWS and Google Cloud or similar platforms.
Cloud Architecture:
Experience in designing and integrating systems with appropriate security measures.
Strong understanding of cloud service components from an architectural perspective (how they work, capabilities, and limitations).
Expertise in developing systems using cloud services, especially AWS (preferred), GCP, or Azure.
Tools Proficiency:
Project Management: JIRA Cloud, Miro.
Monitoring and Logging: Datadog, Cloud Monitoring, CloudWatch.
Configuration Management: Terraform.
CI/CD: GitHub Actions.
Documentation Tools: Kibela, Google Workspace.
Experience with Key Technologies:
Spark: 2–3 years of experience.
Airflow: 1 year (as a user, not an administrator).
Project and Team Management:
Led a team as a Data Engineer Lead (minimum of 2 members for at least six months; larger teams and longer durations are a plus).
Experience as a Project Manager or Product Manager.
Communication Skills:
Proficient in English with a certification level of IELTS 7, TOEIC 800, or equivalent.
Open- minded with a strong capability to understand the purpose and details of tasks.
