Description
Hồ Chí Minh
Full-time
What you will do:
Create and maintain optimal data pipeline architecture, data management tools;:
Create, maintain, and optimize data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.:
Assemble large, complex data sets that meet functional / non-functional business requirements;
- 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 optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Hadoop, Spark, Apache Iceberg and other ‘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;
- Keep our data separated and secure as well as ensure data quality, data security and data privacy;
What you will need:
Experience in building API, software services/tools for data management, data governance:
Advanced working Hadoop, Spark knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases;
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets. Experience of Open Lineage, Open Metadata, Apache Doris, Apache Airflow is a plus;
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement;
- Strong analytic skills related to working with unstructured datasets;
- Build processes supporting data transformation, data structures, metadata, dependency and workload management;
- A successful history of manipulating, processing and extracting value from large disconnected datasets;
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores;
- Strong project management and organizational skills;
- Experience supporting and working with cross-functional teams in a dynamic environment.