Check with seller Big Data Technical Lead Quận 1

Mô tả công việc Create and maintain optimal data pipeline architecture. 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 and AWS 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. Assemble large, complex data sets that meet functional / non-functional business requirements. 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 data and analytics experts to strive for greater functionality in our data systems. Quyền lợi được hưởng - Company trips, team building. - Competitive salary - Other benefits according to the provisions of the Company and the Labor Code. Yêu cầu kỹ năng Advanced working SQL 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 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. Experience with big data tools: Hadoop, Spark, Hive, etc. Experience with relational SQL and NoSQL databases including Postgres, SQL Server, Oracle, MySQL, Solr, Elasticsearch, Cassandra. Experience with data pipeline and workflow management tools: Luigi, Airflow, etc. Experience with stream-processing systems: Storm, Spark-Streaming, Kafka, etc. Experience with object-oriented/object function scripting languages: Python or Java. Having knowledge in the financial market, or the stock market will be a plus (but don’t worry if you haven’t, you can learn all about how to be a successful stock investor after joining us!).

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