• Building a Cloud sourcing system that pulls data from tens of thousands tables on-premises, and hundreds of data source systems (RDBMS, file server, Kafka,...) Designing change data capture method for each source system
• Designing and implementing a Big Data management system by leveraging Lambda/Delta/Kappa Architecture concept
• Implementing data replication/projection lag from Techcombank on-premises to Techcombank Data lake on Cloud in real-time processing or batch model with high performance - scalable AWS services like Kinesis, Firehose, Glue (Spark), Lambda,...
• Serving analytics data of ten million Techcombank customers to other Techcombank internal teams, providing hundreds of millions of data elements daily through high throughput, low latency protocols (WebSocket, message queue, REST, GraphQL,...)
• Collaborating with the Data Architect team on regular basis to design/review data models, and application architectures 
• Maintaining software clean architecture, clean code, and high quality. Participating in code reviews, pair programming, mob programming, and coaching other members
• Providing data features infrastructure to empower ML engineering in various bank businesses

Must have:

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Technology, or a related technical field
• Have 6+ years of experience as a Data Engineer or Software Engineer
• Extremely proficient in at least 1 programming language (Java, Scala, Python)
• Strong experience in systems architecture – particularly in complex, scalable, and fault-tolerant distributed systems
• Good at multi-threading, atomic operations, computation framework: Spark (Dataframe, SQL, ...), distributed storage, distributed computing
• Understand designs of resilience, fault-tolerance, high availability, and high scalability, ...
• Tools: CI/CD, Gitlab, ...
• Good at communication & team working
• Being open-minded, willing to learn new things

Bonus points:

• Cloud experience (AWS, GCP, etc), AWS is a plus
• Experience in performance tuning/optimizing Big Data programs
• Having knowledge of distributed query engines: Presto, Hive, ...