Onpoint

Overview of job

Reporting to the Head, Data Analytics Centre of Excellence you will be responsible for :

·       Develop and continuously improve data pipeline architecture, including data crawling with RESTful API and web scrapping, data ETL / ELT, Data Lake / Data Warehouse / Data Marts, DataOps / MLOps.

·       Perform technical review, coaching and guidance to Data Engineers who participate in various agile Squads. Provide technical expertise to enable Data Engineers to resolve blockers or impediments.

·       Ensure that the Data Engineers design and implement scalable data pipeline solution in accordance to architecture, technology standards and best practices. Data pipeline must be able scale to assemble large, complex data sets from 1st, 2nd and 3rd party data sources in real-time.

·       Setup DataOps / MLOps to accelerate the continuous integration and continuous deployment of Data Engineering and Machine Learning solutions. Collaborate with Data Engineers, Data Scientists and Data Analyts to onboard onto DataOps and MLOps.

·       Setup automated monitoring solution to continuously monitor reliability, availability and performance of Data pipelines components and processes. Able to detect incidents in real-time, so that incidents can be resolved in near real-time.

·       Ensure processes related to incident management and problem management are in place, including Service Level to ensure incidents and problems are resolved timely in accordance to Service Level.

• An opportunity to learn at a company that is growing for regional scale (South East Asia)
• Working in a young, super talented and supportive team environment
• Attractive salary (Up to 2500 USD)
• Company trip, team building
• PTI Insurance
• Macbook Pro for Developer
• Bonus project
• Bonus KPI/Month

In order to succeed in the role, you should ideally have:

·       Degree in Computer Science, Computer Engineering, Information Systems or another quantitative field.

·       More than 6 years hands-on engineering experience, with at least 3 years in Data Engineering.

·       At least 2 years in people management experience.

·       Hands-on experience with designing and implementing data pipeline on AWS Stack, including, AWS S3, Lambda, EC2 / Fargate, EKS, Glue, RDS Aurora, Redshift, Cloudwatch.

·       Hands-on experience with 1 or more of the following tools and libraries – Airflow, Airbyte, Selenium, Python, Java, JavaScript, ELK, Apache Kafka, SQL, Apache Spark.

·       Experience working with Agile development framework.

·       Good communication skills with stakeholders, including various Technology teams, Data Analysis teams, Business teams.

·       Able to communicate fluently in Vietnamese. Fluency in English is an added advantage.