Data Pipeline Engineer for Financial Analytics

Cornerstone Global Partners

Hong Kong

On-site

HKD 450,000 - 650,000

Full time

44 hours ago
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Job summary

Cornerstone Global Partners is seeking a data engineer to design, build, and maintain scalable data pipelines and ETL processes. You will work with data scientists and analysts to understand data needs and deliver actionable insights.

The role requires expertise in SQL, relational databases, and data warehousing, with hands-on experience in Spark and Kafka. Collaboration with stakeholders and strong data governance will be essential.

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 banking/finance.
  • Proficiency in SQL and experience with relational databases (PostgreSQL, MySQL).
  • Familiarity with data warehousing (AWS Redshift, Google BigQuery).
  • Experience with ETL tools (NiFi, Talend, Informatica).
  • Programming languages for data manipulation (Python, Java, Scala).
  • Experience with data processing frameworks (Spark, Kafka).

Responsibilities

  • Design, build, and maintain scalable data pipelines and ETL processes.
  • Manage and optimize databases for storage, retrieval, and security.
  • Collaborate with data scientists, analysts, and stakeholders to deliver insights.
  • Implement data quality checks and monitoring for data accuracy.
  • Maintain documentation of data architecture, pipelines, and processes.

Skills

SQL
Python
Java/Scala
Spark
Kafka

Education

Bachelor’s degree in CS/IT

Tools

NiFi
Talend
Informatica

Job description

Cornerstone Global Partners is seeking a data engineer to design, build, and maintain scalable data pipelines and ETL processes. You will work with data scientists and analysts to understand data needs and deliver actionable insights.

The role requires expertise in SQL, relational databases, and data warehousing, with hands-on experience in Spark and Kafka. Collaboration with stakeholders and strong data governance will be essential.

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