Senior Data Engineer
Ho Chi Minh
2016-10-06 -> 2016-06-12
- Your must-haves
- • Bachelor degree in Computer Science or Software Engineering.
- Specialization in data science or a higher degree is a big plus.
- • Minimum 3 years of experience in Software Engineering
- • Comfortable with functional programming (Python or Scala is a plus)
- • Experience with SQL (Postgres is a plus)
- • Experience with NoSQL (Mongo, Redis, Cassandra is a plus)
- • Experience with indexing and retrieve on Search Engine (Lucene or ElasticSearch is a big plus)
- • Good communication skills, able to clearly present complex concepts and insights to less technical-minded team members and external people.
- Your nice-to-haves
- • Knowledge and experience in NLP
- • Knowledge about modern big data technologies (Akka, Hadoop, Map Reduce, Spark, Actor model)
- • Experience in queue system, RabbitMQ is a big plus
- • Experienced in Search engine and Databases (PostgreSQL, Cassandra, HBase, ElasticSearch, MongoDB)
- • Familiar with cloud services such as (AWS, AZURE)
- What we offer:
- • We are a young and fast-growing global company in one hottest VC-areas: FinTech.
- • As the winner of the Swiss FinTech Award 2016 we offer you to work on a world class innovation at the right market timing.
- • We give you an opportunity to shape our future and develop yourself with many options to move to other areas as we grow.
- • We have a talented, international team of top-notch experts.
- • We foster an open communication culture and strive to learn and improve every day. Top modern office in Ho Chi Minh meeting the highest global standards
- Most important:
- • We move fast and have fun while doing it. If you enjoy working with passionate people and seeing the results of your efforts in newspapers daily around the world, you will fit right in.
- Your team and role
- The overall responsibility of the data engineering team is to develop and run on production (1) product / tools related software and (2) the firm’s infrastructure. Although development and production roles are split within the team, members have the opportunity to rotate within these functions. Typically data engineers get involved early when prototypes come out from the data scientist team. In addition a large number of internal tools need to be upgraded and further developed to meet ambitious targets to serve our clients. Such prototypes involve rules-based frame works within NLP, Semantic Web, Event-Detection and a variety of classification problems requiring Machine Learning and Deep Learning approaches. Infrastructure projects mainly include our capability to scale our (micro)services with the help of distributed systems (Akka, Spark, Hadoop).