Associate Data Engineer (SQL)
Fl 8-Unit 802, Tòa nhà Beautiful Saigon, 2 Nguyễn Khắc Viện, Phường Tân Phú, District 7, Ho Chi Minh
Không xác định
2020-05-01 -> 2020-05-02
- Demonstrate knowledge and real-world experience on Big data technologies. A successful history of manipulating, processing and extracting value from large disconnected datasets.
- - Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- - Strong analytic skills related to working with unstructured datasets.
- - Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
- - We are looking for a candidate with > 2+ years of experience in a Data Engineer role. They should also have experience using the following software/tools:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL databases such as Oracle, SQL Server, MySQL or Postgres.
- Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- - Some experience on visualization tools such as PowerBI/Tableau or other BI tools will be beneficial.
- - Degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field
- - 2+ years of relevant experience.
- Collaborate with customer to gather requirements and to understand their business processes.
- Create and maintain optimal data pipeline architecture,
- 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 Spark, SQL and Azure ‘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.
- Use tools to deploy and monitor the performance of the systems in production.