Do you have a good grasp on Database or SQL, and enjoy building automation? Come join our fast-growing team! With opportunities in both Singapore and Hong Kong, we’re hiring Analytics Engineers within our Data Engineering team that are an essential conduit to other engineering teams across our consumer-facing company, as well as our Data Insights team.
About the Data Engineering Team
Our team acts as a central nexus to connect various data producers with consumers across the company. Our customers are:
- Other engineering teams across the company that produce or consume data that need to be combined with other data sources.
- Analysts within the Data Insights team.
- Business Stakeholders in various other teams (finance, marketing, and others)
We are accountable for delivering:
- A centralized data platform that enables engineers and analysts across the company to ingest, anonymize, and enrich with other data sources from anywhere else in the company, and to persist, analyze, purge, and otherwise process their data.
- Tools, training, and coordination.
- Data applications that don’t fall into any one business unit, or where the business units don’t have sufficient capabilities themselves. For example, we team up with the Data Insights team to build and operate churn-prediction models used by both humans and other systems at scale.
- Data Catalog for documenting the sources of data and what is available for use by other teams.
Our responsibilities include:
- Building and operating the data platform service, including defining and tracking its SLA.
- Guiding various engineering teams to design models and schemas of the data to be fed into the platform, making sure they can be processed in a scalable way and used by analysts efficiently.
- Guiding data analysts on the use of the data platform.
- Building libraries/modules and reference implementations of data ingesters on several common tech stacks.
- Guarding user privacy. While all teams are responsible for ensuring compliance of their work with our privacy policy, our team also has a veto right against processing any data that might not be compliant.
- Partnering with other teams on projects to build data engineering solutions such as for churn-prediction, payment fraud management, and other company-wide challenges.
Other notes about our team:
- Our tech stack currently mostly focuses on AWS Redshift, Google BigQuery, Apache Airflow, Athena, dbt and Tableau
- We have an ever-expanding range of engineering roles on the team, covering people with backgrounds in software development, infrastructure operations, data modeling and data science.
Key Responsibilities
Your responsibilities will include:
- Understand the business requirements of your customers, and convert them to well-defined, maintainable and extendable data models.
- Deliver well-defined, transformed, tested, documented and high-performing data models.
- Develop orchestration to construct data models in adherence to their SLA and dependencies.
- Apply engineering best practices to data models.
- Collaborate with Data Engineers to improve and streamline the data platform.
- Implement and maintain data quality standards and data governance practices.
- Maintain data documentation and definitions.
- Training other members of the organization (data engineers, data analysts, key stakeholders) to ensure they have the skills to effectively navigate, locate, and utilize data within the established data models.
Requirements
- Proficiency in SQL, with a solid understanding in query optimization
- Proficiency in Data Modelling
- Experience in working with data warehouses Redshift, BigQuery, Snowflake, etc.
- Experience in data analytics and data visualization tools is a big plus
- Experience in dbt (data build tool) is a big plus
- Experience in Python is a big plus
- Good command of written and spoken English
