The Data Science and Engineering team of Gigatum is dedicated to help Clingme users to find and ultimately purchase the right products and services. We are tasked with tackling one of the most complex problems of e-commerce: bringing up the right products for the right consumer at the right time in milliseconds. We are looking for an experienced Data Engineer/Architecture to join our team to build analytics and machine learning infrastructure that supports e-commerce application of millions of consumers every day.

You will have opportunities to collaborate with and be advised by experienced Data Scientists from Silicon Valley, with decades of experience in big data, AI and machine learning.

Responsibilities and Duties

You will play a critical role in leading the design and building of the underlying engineering and data infrastructure to support a wide range of machine learning and search capabilities. Your responsibilities include but not limited to

  • Design/architecture large-scale distributed computing and data base infrastructure to support end-to-end data mining and machine learning solutions to support millions of consumers

  • Lead development, coding, testing and debugging solution related to our Data solutions

  • Improve/redesign current data model for explosive growth in data

  • Develop, enhance and maintain the data pipeline - ingestion, transformation, storage, analysis and visualization using combination of open source and paid technology tools

  • Implement automating data solutions including KPI reporting, streamlining integration of external data sources

Qualifications and Experience

  • MS or PhD in Computer Science or equivalent degree (BS degree is OK with substantial working experience).

  • 3+ years (preferred 5+) of experience in designing and developing distributed systems/applications, preferably in an eCommerce domain.

  • Experience in architecture and building large-scale data pipelines which process millions of events per day using Java, Python, and/or SQL.

  • Understanding of data flows, data architecture, ETL and processing of structured and unstructured data.

  • In-depth knowledge of Big Data distributions and experience in SQL/NoSQL/BigQuery.

  • Familiarity with Airflow, Kafka and stream processing systems such as Storm, Spark and cloud Data stores such as Amazon Redshift.

  • Experience with cloud computing including AWS (or similar cloud solutions) infrastructure and services, micro-services architecture.

  • Should possess strong computer science fundamentals: data structures, algorithms, programming languages, distributed systems, and information retrieval.

  • Direct experience or experience collaborating with data scientists to perform in data mining and machine learning would be a strong plus.

  • Experience with MongoDB, Elastic Search, Business Intelligence and reporting tools would be a plus.

About Clingme

Gigatum is transforming consumer experiences in Vietnam by bringing together state-of-the-art mobile app design, social-networking, big data and Artificial Intelligence (AI) to create intuitive and personalized shopping experience for consumers and improve revenue generation for merchants. We enable friendly and easy ways to connect millions of consumers and local merchants. In the center of our ecosystem is Clingme – Đi gần Chọn đúng, a mobile application with multiple features designed to improve consumer experience, including cash back, local search, product recommendation and review.

We are celebrating our 4rd birthday with 3 rounds of funding; the latest is series A with 2.5 million USD investment. We have signed up world-class investors who are also our priceless advisors. We are a team of mobile product specialists; big data experts and football enthusiasts, passionate about building mobile products that make life more enjoyable.




Head Office

  •   8 Unit 8 Floor TNR Building,
  •         54A Nguyen Chi Thanh,
  •         Dong Da, Ha Noi


  •   5B Floor, GB Building,
  •         78-80 Cach Mang Thang 8,
  •         W.6, D.3, Ho Chi Minh City


  •   093 461 0125