Location : Singapore
About the Role:
We are looking for a savvy Data Engineer to who will be part of the Company, a new team being set up in the Singapore Office. This team will pioneer the Digital Transformation initiative for our product, sales, leadership and marketing teams with insights gained from analyzing company data. You will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoy optimizing data systems and building them from the ground up. The data engineer will support our software developers, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.
Create and maintain optimal data pipeline architecture.
Maintain data security, integrity and operations of systems over their life-cycle.
Assemble large, complex data sets that meet functional / non-functional business requirements.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and ‘big data’ technologies.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
Work with data and analytics experts to strive for greater functionality in our data systems.
5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
C++/C#: high-performance language is at the heart of our data engineering operation. Parallelizing computations and developing distributed systems using C++ enables us to take full advantage of working with big data
Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
Big Data tools: Hadoop, Spark, Kafka etc.
Experience in using R for speed when taking strategies from the exploration to production and using the data.table package.
Using Python for automated data manipulation
Experience with relational SQL and NoSQL databases, including Postgres, Neo4j and Cassandra.
Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.