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Data Analytics Engineer
3 months ago
The Data Analytics Engineer is a key role in developing data analytics capabilities and enhancing our enterprise data platform. This position requires a strong technical background in cloud experiences and data domain technologies, as well as excellent problem-solving skills to ensure solutions are scalable, secure, and efficient.
Key Responsibilities:
- Design and implement scalable and secure data analytics solutions for data ingestion, data processing, data visualization, and analytics.
- Collaborate with stakeholders to deliver data platform capabilities, prioritizing requirements based on business benefits and protection against data risks.
- Promote compliant and quality reuse of data on the enterprise platform, through incremental delivering functionalities in data lifecycle, including data access control, data lineage, data modeling, data quality, and data analytics.
- Apply native cloud skills like container, object storage, and DevSecOps to enable effective data analytics, data management, and data governance.
Requirements:
- Bachelor's degree in computer science, technology, data, or related disciplines.
- 5 years of working experience in systems development, preferably in large enterprises.
- Well-versed with SDLC project disciplines and experienced in Agile methodologies in cross-functional teams.
- Good understanding of enterprise data architecture and technology stack, covering batch processing and streaming data for analytics usage.
- Familiar with cloud technology and operations in AWS, Azure, or China clouds and data processing in a cloud environment.
- Solid technical background with hands-on experience in software development and data-related technologies.
- Proficiency in programming languages such as Python, Java, C++, or Scala.
- Hands-on experience with big data technologies and ecosystems, including Hadoop, Spark, and Kafka.
- Knowledge of database systems, both relational and NoSQL.
- Familiar with big data technologies, e.g., Redshift, HDFS, HBase, Hive, etc.
- Experience in data security and data management tools, e.g., LDAP, OAuth, Keycloak, Lake Formation, etc.
- Experienced in DevSecOps tooling, CI/CD pipeline, Terraform, etc.
Location:
Hong Kong Exchanges and Clearing Limited - Exchange Square
Shift:
Standard - 40 Hours (Hong Kong SAR)
Scheduled Weekly Hours:
40
Worker Type:
Permanent