Job description
About Us
We are seeking a motivated and skilled Mid-Senior Big Data Engineer to join our dynamic team. In this role, you will work closely with Solution Architects to develop innovative and scalable solutions for our customers. The ideal candidate will be available to work directly with customers in foreign countries, ensuring high-quality solutions and seamless collaboration.
Key Responsibilities:
路聽聽聽聽聽聽聽 Develop and implement Big Data solutions using technologies such as Python or Java, and SQL.
路聽聽聽聽聽聽聽 Support and collaborate with Solution Architects to develop optimal customer architecture solutions.
路聽聽聽聽聽聽聽 Leverage Data Visualization tools (PowerBI, Tableau, Grafana) to build meaningful insights from data analysis scenarios.
路聽聽聽聽聽聽聽 Apply knowledge of real-time data ingestion technologies to design efficient data flows.
路聽聽聽聽聽聽聽 Work within the Hadoop ecosystem (HDFS, MapReduce, Hive, Spark) to process and analyze datasets.
路聽聽聽聽聽聽聽 Design, implement, and maintain ETL/ELT pipelines.
路聽聽聽聽聽聽聽 Work with data storage formats such as ORC, Parquet, and CSV.
路聽聽聽聽聽聽聽 Collaborate with internal teams to explain and demonstrate Huawei Cloud Big Data capabilities.
路聽聽聽聽聽聽聽 Engage with customers in foreign countries, providing on-site or remote support and ensuring high-quality customer service and solution implementation.
路聽聽聽聽聽聽聽 Troubleshoot and optimize batch processing workflows using Hive, Spark, and other Big Data technologies.
Required Qualifications:
BSc or MSc degree in Computer Engineering, Computer Science, Software Engineering, or a related technical field.
路聽聽聽聽聽聽聽 Minimum of 3 years of professional experience in Big Data engineering, with hands-on experience in Spark, Flink, Hadoop, and related technologies.
路聽聽聽聽聽聽聽 Have a knowledge in Python or Java programming languages.
路聽聽聽聽聽聽聽 Have an experience with SQL development (MySQL, PostgreSQL).
路聽聽聽聽聽聽聽 Hands-on experience with batch processing using Hive, Spark.
路聽聽聽聽聽聽聽 Knowledge of Data Storage Formats (ORC, Parquet, CSV).
路聽聽聽聽聽聽聽 Have a knowledge in Data Visualization tools (PowerBI, Tableau, Grafana) for building meaningful insights from complex data.
路聽聽聽聽聽聽聽 Experience with Data Warehousing and Data Lakes concepts.
路聽聽聽聽聽聽聽 Ability to communicate effectively and present technical concepts to both technical and non-technical audiences.
路聽聽聽聽聽聽聽 Experience working in Unix/Linux environments.
路聽聽聽聽聽聽聽 Fluency in written and spoken English is a must.
路聽聽聽聽聽聽聽 Enthusiasm for continuous learning and sharing knowledge with colleagues.
路聽聽聽聽聽聽聽 Familiarity with real-time data ingestion systems (Kafka, RabbitMQ) is a plus.
Seniority Qualifications:
路聽聽聽聽聽聽聽 Solid understanding of ETL/ELT methodologies and data processing best practices.
路聽聽聽聽聽聽聽 Designing and implementing complex pipelines in Data Warehouse and Data Lakes.
路聽聽聽聽聽聽聽 Comprehensive knowledge on open source Big Data product management. ( Hadoop(Flink,Hive,Spark, Clickhouse))
路聽聽聽聽聽聽聽 Comprehensive knowledge about Apache Hudi, Iceberg.