Megazone

Tóm tắt công việc

MEGAZONE Vietnam is looking for a highly skilled Data Engineer with strong experience to join our dynamic global team. The ideal candidate will be responsible for building, and optimizing large-scale data pipelines, ensuring scalability, performance, and reliability. You will serve as a technical engineer and consultant, collaborating closely with external clients, offshore teams, and partners

What You Will Do:

• Collaborate with AI engineers, data scientists, and business stakeholders to understand data requirements and deliver clean, reliable, well-architectured data
• Design and develop distributed data pipelines for batch and streaming data
• Build and maintain highly scalable and secure Big Data platforms
• Develop data processing jobs using Apache Spark (Spark SQL, DataFrame, Dataset, Structured Streaming)
• Optimize data pipeline jobs for performance, memory, and cost
• Work with large datasets (TB–PB scale)
• Build streaming pipelines using Kafka / Kinesis / Pulsar (if applicable)
• Mentor junior engineers and review code to ensure best engineering practices are followed.
• Lead technical workshops and training sessions to enable client teams on best practices.

Basic Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or related field.
• 1- 5 years of experience in data engineering, Big Data, AI.
• Strong understand knowledge of Big data, distributed data, data platform
• Strong proficiency in SQL and Python skills.
• Experience with cloud platforms: AWS, Azure, or GCP (preferably AWS).
• Familiarity with CI/CD, Git, and DevOps practices for data system
• Hand-on experience with OLAP: ClickHouse, Redshift, BigQuery, Snowflake (at least one)
• Experience with real-time data processing ( Kafka, Kinesis, Spark Streaming..).
• Experience deploying data workloads on cloud
• Excellent communication and presentation skills to effectively interact with business stakeholders and
  clients.

Preferred Qualifications

• Knowledge of data security, privacy, and compliance practices.
• Experience with Lakehouse architecture
• Experience Optimize performance at scale
• Exposure to machine learning pipelines and MLOps concepts
• Understanding of MLOps best practices and AI model lifecycle management.
• Knowledge of data governance frameworks and metadata management.