COMPANY OVERVIEW
Lynx Analytics was founded in 2010 by a group of INSEAD students and professors with a strong research background in graph analytics. Several of our founders since then became professors and faculty directors of analytics centers at leading US universities. Our founding purpose? To apply graph theory to simplify and solve complex, real-world business problems.
Our mission has evolved over the years, and we currently offer a range of cutting edge data analytics and AI solutions to help companies transform their operations and optimise their commercial performance. Back then, graph theory was mostly the purview of social networking sites. We wanted to expand this technology and help companies leverage their communities to unlock greater growth.
Lynx has offices in Singapore, US, Hong Kong, Hungary, and operations in several other countries such as Canada, Germany, Indonesia. We work with some of the world’s largest companies and are constantly looking to expand our knowledge base and geographical footprint. Lynx Analytics’ technology is deployed with various Clients internationally and has significant growth potential.
We have a diverse and inclusive global team comprising Professors, PhDs, MSc’s, and MBAs from Ivy Leagues, INSEAD and NUS with a broad spectrum of experience in start-ups and blue-chip companies (Google, Databricks, ZS, Abbvie, Amgen, Vodafone, Morgan Stanley, Palantir, Katana Graph to name but a few). It is the combination of our industry insight and experience, scalable proprietary technology, and highly qualified people that drives our compelling value proposition.
We are looking for ambitious, innovative, empathetic and relentless team players to explore the career opportunities that we offer as we continue to scale our operations.
KEY RESPONSIBILITIES
As a Senior Data Engineer, your responsibility is to implement and deploy data analysis pipelines at various clients of Lynx Analytics. In this role, you will
- Understand the business problems we solve for our client. This role involves frequent communication with our client, and a close working relation with the Data Scientist.
- Discover the client's existing data sources that are relevant to the problem we try to solve. This includes discussions with client IT, data owners, future business users, etc.
- Together with IT employees of our client, decide on the technical architecture for the ETL solution.
- Implement the data ingestion subsystem: this is the system responsible for moving all the necessary data sources to a single location where the actual analysis will happen.
- Implement the data analysis pipelines using standard Big Data technologies (Spark, Airflow)
- Perform feature engineering to transform raw data into features that better represent the underlying problem to predictive models.
- Provide the underlying infrastructure (DevOps)
REQUIREMENTS
- 5-6 years or more of Data Engineering experience
- BS or Master's degree in a relevant field (Computer Science, Software Engineering, or similar)
- Experience in GCP, Airflow and Spark
- Solid experience in Python and SQL
- Experience in project delivery to business customers
- Strong problem-solving and communication skills will be needed.
WHAT WE OFFER
- Opportunity to expand your knowledge of data engineering tools and platforms using state-of-the-art tech stack
- Create innovative solutions, take ownership of significant projects
- Work with large multinational clients globally. If you enjoy traveling around the globe, you will have the opportunity to do so
- Be a member of a very strong team including senior technology experts, mathematicians, ex-Googlers, Ivy League professors and telecommunications industry experts
- Startup atmosphere - collaborative company culture, openness for innovation, direct access to company management
