Data Engineer - Tech in Asia｜Meet.jobs

Tech in Asia is building up our internal analytics products to deliver better data and insights to our users and the editorial team.

We are looking for an experienced Data Engineer to join our growing team, who 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 Data Engineer will support our software developers, database architects, data analysts, and data scientists on data initiatives and will ensure the reliability and quality of data. They must be self-directed and will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.

In this role, you will:

• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for ETL processes from a wide variety of data sources.
• Work with stakeholders including the Executive, Product and Marketing 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.

Requirements:

• Advanced working SQL knowledge and experience working with relational databases and familiarity with a variety of databases.
• Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets.
• A successful history of manipulating, processing, and extracting value from large disconnected datasets.
• We are looking for a candidate with 2+ 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
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Hive.
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.