This is a great position for tech enthusiasts like you. This position will have chance to deal tons of data from mobile operators and digital ads ecosystem, or develop services to handle high concurrency requests.
These are tasks this position may be in charge or collaborate with others members:
1. Develop in-house tools or use 3rd party tools for data acquisition, processing, modeling, monitoring.
2. Develop backend service and collaborate with frontend engineers to delivery product features.
3. Align and optimize data pipeline architecture for data collection, cleaning, storage, processing and analytics with business requirements.
4. Develop and integrate scalable, reliable, maintainable web-service backend systems with current data processing framework to represent data insights.
5. Identify ways to improve data reliability, efficiency and quality.
6. Document architecture design and features implementation.
7. Deploy sophisticated analytics programs, machine learning and statistical methods to find hidden patterns using data.
8. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
We will need you to have some of the following skills or experience:
1. Experience in hands-on ETL task design, components and modules development of data process
2. Ability to build services in Linux/Unix environments and familiar with shell script
3. Familiar with at least one programing language for backend development, such as Golang, Javascript (with Node.js), etc.
4. Experience of database table design and performance tuning
5. Experience in operating large scale distributed systems or applications
6. Positive, can-try attitude, good communication skill to cowork with talent team members
1. Experience as a data engineer or in a similar role
2. Experience in Scala development
3. Familiar with Hadoop ecosystem, such as Spark, Hadoop
4. Experience in performance tuning via algorithm or architecture improvements
5. Experience with Cassandra, Clickhouse, Redis
6. Experience in kubernetes as a devops engineer
7. Experience with Kafka, Prometheus, Grafana
8. Experience in unit test, integration test, security test, stress test
9. Advanced database schema design knowledge, data sharding, replica usage, etc.
10. Numerical and analytical skills
11. Experience in implementing data mining and machine learning algorithm
One might want to test the environment before the interview.
Interviewees can bring their own laptops or use the MAC provided by GT.
2. The tech lead of the team will introduce the current software structure
and then ask some technical questions.
3. Interview with the BU head.