APPLICATION DEVELOPER

Junior Data Engineer

Responsibilities

1. Data Pipeline Development & Maintenance

• Participate in the development and optimization of both batch and real-time ETL/ELT processes.
• Support the reliable extraction, transformation, cleansing, and loading of data from various business systems into the data warehouse and data lake.

2. Data Modeling & Data Asset Development

• Assist in dimensional modeling for enterprise data warehouses under the guidance of senior team members.
• Contribute to the design and development of fact tables, dimension tables, and aggregate tables.
• Maintain standardized data dictionaries, technical documentation, and data governance artifacts.

3. Data Quality Assurance

• Support the implementation of data quality monitoring frameworks.
• Assist in defining and maintaining validation rules for data completeness, accuracy, consistency, and timeliness.
• Collaborate with the team to identify, analyze, and resolve data quality issues in a closed-loop manner.

4. Data Platform Technology Implementation

• Participate in the learning, evaluation, and implementation of modern data platform technologies, including Spark, Flink, Kafka, Airflow, Snowflake, and related tools.
• Assist in building CI/CD pipelines, automated testing capabilities, and engineering best practices for data platform development.

5. Cross-functional Collaboration & Delivery

• Work closely with Product, Data Analytics, and Backend Engineering teams to gather requirements and participate in technical solution discussions.
• Translate complex business requirements into scalable and maintainable data solutions.
• Provide support for day-to-day platform operations, troubleshooting, and incident resolution.

Qualifications

Education

• Graduating in 2026 with a Bachelor’s degree or above from an accredited domestic or international university.
• Preferred majors include Computer Science, Software Engineering, Mathematics, Statistics, Data Science, or related disciplines.

Programming & Database Fundamentals

• Solid foundation in computer science principles and database concepts.
• Proficient in SQL for data querying and manipulation.
• Strong proficiency in at least one mainstream programming language (Python, Java, or Scala).
• Demonstrates good coding standards, software engineering practices, and object-oriented programming skills.

Big Data Technology Knowledge

• Strong interest in big data technologies and data engineering.
• Familiar with the core concepts and use cases of Hadoop, Spark, Flink, Kafka, and related ecosystem components.
• Experience with cloud platforms (AWS, GCP, Azure) and/or cloud data warehouses (Snowflake, BigQuery) is a plus.

Data Engineering Fundamentals

• Understanding of data warehousing concepts, including dimensional modeling, star schema, and snowflake schema design.
• Familiarity with Linux operating systems, common shell commands, and Git version control.
• Knowledge of Docker containerization and CI/CD concepts is considered an advantage.

Soft Skills

• Excellent analytical thinking and problem-solving abilities.
• Strong communication skills with the ability to explain technical concepts clearly to non-technical stakeholders.
• Demonstrates accountability, ownership, and a proactive mindset.
• Ability to work effectively in a fast-paced environment and manage multiple priorities simultaneously.

Preferred Qualifications

• Previous internship experience in Data Engineering, Data Platform, Data Warehouse, or Big Data-related roles.
• Contributions to open-source projects.
• Outstanding achievements in data-related competitions, hackathons, or technical challenges.