Data Engineer Lead
Fave is one of Southeast Asia’s fastest growing start-ups. Having served tens of thousands of offline businesses and millions of consumers, Fave is now one of the leading mobile O2O platforms in the region.
With operations across the region including Malaysia, Indonesia, and Singapore, this is a rare opportunity for you to be part of a larger Southeast Asian story. At Fave, we believe that small and medium businesses are the backbone of the economy and we have made it our mission to help offline businesses across SEA to go and grow online.
Hustling in a fast-paced startup environment can be incredibly rewarding. At Fave, we make it all the more fun with offices designed for collaboration, productivity, and play. You get unlimited access to people (founders included), opportunities to learn, coffee, and WiFi – and we consider these the basic necessities! There’s also an office pool table, ping pong, PS4 console, FaveUp learning sessions featuring industry veterans, movie nights, and lots more!
We are looking for an experienced software engineer to lead the data engineering efforts at Fave. You will be part of the Data team and together bring the data infrastructure/processes that allow Fave to scale to greater heights. The ideal candidate should have experience in distributed computing, storage architectures and be able to think at scale
If being a part of a digital revolution in the fastest-growing region in the world excites you, get in touch today!
Generally as someone in the data team,
- You’re data-driven and/or are comfortable with basic statistical principles and applying them to data sets.
- You are comfortable working in a team, or on your own, and not afraid to be honest when you don't know something (We encourage saying "I don't know, but I'll figure it out!").
- You are excited when faced with a task you don't know how to accomplish. Your mind races with potential solutions, and their respective pros and cons.
As the Data Engineer Lead, you will:
- Own, architect and scale Fave’s data platform.
- Manage our data warehouse/lake, ETL processes, and data pipelines.
- Evaluate and optimize performance and scalability of data pipelines ensuring accuracy and stability.
- Manage and maintain analytics/BI tools/platforms, e.g Tableau, Looker, etc.
- Develop real-time and batch data ingestion from multiple data sources and processing pipelines to be used for analysis, machine learning, dashboards, alerts, and visualizations.
- Work closely with partner teams to establish the optimal technical solution to business problems.
- Mentor and technically manage the data engineering team.
- Basic understanding and overview of statistical methods and machine learning algorithms.
- Experience with data science workflows and deploying machine learning models into production (Docker, Airflow, Pachyderm, Sagemaker, etc).
- Experience building, operating and optimizing distributed, large-scale data storage and analytics solutions using Amazon Web Services (e.g. S3, EC2, EMR, Redshift, RDS, DynamoDB, Athena, Glacier, Elasticsearch, etc).
- Strong command of SQL and database concepts.
- Experienced in Python development.
- Knowledgeable in API development.
- Experience with SOA and micro-services would be a plus.
- Understanding of the e-commerce industry and marketing technologies (ad-serving, attribution modeling, etc) would also be a plus too.