Data Engineer (Major Bank)
Summary
Data engineer at a major bank in Hong Kong who designs, builds, and maintains scalable ETL pipelines and databases, ensures data quality and documentation, and partners with data scientists and business stakeholders. Core stack: SQL, relational databases, cloud data warehouses, ETL tools, Python/Java/Scala, and Spark/Kafka.
Design, build, and maintain scalable data pipelines and ETL processes to collect, process, and transfer data from various sources.
Manage and optimize our databases to ensure efficient data storage, retrieval, and security.
Work closely with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights.
Implement data quality checks and monitoring to ensure accuracy and integrity of data.
Maintain comprehensive documentation of data architecture, pipelines, and processes.
Qualifications:
Bachelor’s degree in Computer Science, Information Technology, or a related field.
3+ years of experience in data engineering or similar roles, preferably in the banking or financial sector.
Proficiency in SQL and experience with relational databases (e.g., PostgreSQL, MySQL).
Familiarity with data warehousing solutions (e.g., AWS Redshift, Google BigQuery).
Experience with ETL tools (e.g., Apache NiFi, Talend, Informatica).
Knowledge of programming languages (e.g., Python, Java, Scala) for data manipulation and transformation.
Experience with data processing frameworks (e.g., Apache Spark, Apache Kafka).