Data Engineer at Shipper

About Shipper

Shipper is a logistic aggregator platform, solving problems for merchants, customers, and third party logistics. We provide also first mail delivery services. We are a growing start-up. We work hard and fast. Responsibility with access to help from all team members is definitely there. We are looking for your awesomeness and your creativity. We trust the work to you and when you have problem, you can ask for help. When you don't know what you are doing, we will guide you on how things could possibly be done. Saying "no" to a logic could be a great thing when it's supported by facts. We support open policy and we are happy to talk about anything. We mean anything and we mean it.

Responsibilities

• Design and develop regular reports and actionable dashboards to track business performance
• Responsible for advanced data analytics and statistical modeling to extract insights from data that results in better logistics services
• Use the quantitative skill sets to drive product roadmap and development
• Evaluate data management in Shipper Logistics organization
• Filter, clean and continuously manage data by reviewing data sources across different tools and systems
• Acquire data from primary or secondary data sources and maintain databases
• Own and manage multiple data initiatives and projects both on an ongoing and ad-hoc basis

• Bachelor degree in Computer Science, Business Analytics or related quantitative fields (Mathematics, Economics, Computer Science, Information Management or Statistics).
• Ability to write complex SQL queries and preferably experience with MySQL, PostgreSQL, MongoDB and data visualization tools (Chartio, Tableau, etc).
• Proficiency in one or more programming languages including but not limited to Python, R
• Strong communication and presentation skills
• Experience with ETL process is a plus
• Experience with AWS ecosystem is a plus
• 3-5 years of experience in an analytical role
• Detail oriented, analytical and inquisitive
• Language: Fluent in verbal and written in English & Indonesian