Middle Data Engineer Công ty Cổ phần GEM

Data Pipeline Development

• Develop, maintain, and optimize data pipelines and ETL processes to ensure efficient data flow and integration.
• Work with structured and unstructured data from various sources.

Data Management

• Ensure data integrity, accuracy, and consistency across all data systems.
• Implement and monitor data quality checks to maintain high standards of data quality.

Collaboration

• Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
• Assist in integrating data from different sources into a unified data warehouse.

Performance Optimization

• Optimize data processing workflows and database performance.
• Identify and resolve data-related issues and bottlenecks.

Documentation

• Create and maintain documentation for data pipelines, processes, and data models.
• Ensure all data engineering practices comply with company policies and industry standards.

Salary: Up to 40M

• Probation salary is 100% of the official salary
• 13th-month salary and performance review twice a year
• Bonus for special occasions each year (Labor Day, National Day, Solar New Year, Lunar New Year)
• Project bonuses
• Employee’s professional certification and training allowances subject to company regulations
• BIC Care Health Insurance
• Annual Health Assessment
• Social, health and unemployment insurance following government policy
• Enjoy company summer trips and other team building activities held monthly and quarterly
• Have chances to gain knowledge on the latest waves of blockchain, AI, Big Data
• Professional, creative and dynamic working environment
• Work five days per week with flexible working time

• Bachelor's degree in computer science, Engineering, or a related field.
• > 2 years of experience in data engineering or a related role.
• Proficiency in programming languages such as Python or Java.
• Strong experience with SQL and relational databases (e.g., MySQL, PostgreSQL, SQL Server).
• Familiarity with big data technologies (e.g., Hadoop, Spark) and data processing frameworks.
• Experience with ETL tools (e.g., Talend, Apache Nifi) and data integration processes.
• Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services.
• Strong problem-solving skills and attention to detail.
• English communication skills, both written and verbal is a plus point.

Preferred Skills:

• Experience with NoSQL databases (e.g., MongoDB, Cassandra).
• Knowledge of data warehousing concepts and tools (e.g., Snowflake, Redshift, BigQuery).
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
• Understanding of machine learning and data analytics concepts.
• Experience with version control systems (e.g., Git) and CI/CD pipelines.
• Certification in cloud data services or big data technologies.