Data Warehouse Engineer

Job Title: Data Warehouse Engineer

Responsibilities:

• Participate in the design and construction of the company's data warehouse.

  Collaborate with the analysis and development teams to engage in data modeling activities, driving the data-driven operations of business departments.

• Collaborate on the development and construction of data application projects for the company.

  Work closely with cross-functional teams to contribute to the development and construction of data application projects, ensuring alignment with organizational goals.

Qualifications:

• Possess a minimum of 4 years of experience in the field of data warehousing.

  Demonstrate proficiency in data warehouse model design and ETL development, including expertise in dimension modeling design methods and hands-on experience in processing massive datasets (ETL).

• In-depth understanding of the knowledge base and skills in the data warehouse domain.

  Exhibit a profound understanding of data collection, data integration, data quality, and data application pipelines.

• Foundation in data modeling and data architecture with familiarity in big data ecosystems.

  Have a solid foundation in data modeling and data architecture, along with familiarity with big data technologies such as Hadoop, Hive, HBase, Spark, Kafka, Flink, Presto, ClickHouse, among others.

• Expertise in SQL with experience in SQL performance tuning, and proficiency in Hive SQL development.

  Demonstrate mastery in SQL, with hands-on experience in SQL performance optimization, and familiarity with Hive SQL development.

• Proficiency in at least one of the following languages: Java, Python, Shell, or Scala.

  Exhibit fluency in at least one programming language, including but not limited to Java, Python, Shell, or Scala.

If you are passionate about data warehouse design, possess a strong analytical mindset, and have the skills to drive data-centric initiatives, we invite you to join our dynamic team at WOO. Be a key player in shaping the future of our data infrastructure and contribute to the success of our data-driven business operations.