Data Engineer (Python, SQL)
315 Trường Chinh, Thanh Xuan, Ha Noi
Không xác định
2021-04-26 -> 2021-04-27
- 2+ years of experience in a Data Engineer role.
- Having a degree in Computer Science, Information Systems, Software Engineering or another related field.
- Wide knowledge about software products using in F&B field is a plus
- Having a degree in Statistics, Informatics is a plus
- Should also have experience using most of the following software/tools/platforms:
- Experience with programming languages such as Python, Scala...
- Advanced working SQL knowledge and experience working with relational SQL and NoSQL databases as well as working familiarity with a variety of data sets: SQL Server, MySQL, PostgreSQL, MongoDB, … etc
- Experience with data pipeline and workflow management tools: Airflow, Azkaban, Luigi...
- Experience with big data tools: Hadoop Yarn, Hive, Spark, Presto... etc
- Experience with both OLAP and OLTP database: design data model, optimization database, optimization query.
- Experience with reporting or BI tools: Zeppelin, Redash, Metabase or PowerBI, Tableau is a plus
- Having Data Engineer certification from major cloud providers is a plus.
- Create and maintain optimal data pipeline architecture
- Extract large, complex data sets that meet functional and non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
- Build the infrastructure required for optimal ETL pipeline from a wide variety of data sources using Python, SQL and Hadoop eco-system technologies.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Work with stakeholders including the Executive, Marketing, Accounting, Finance, etc teams to assist with data-related technical issues and support their data infrastructure needs.
- Work with data scientist and analytics to strive for greater functionality in our data systems