Data Engineer (Innovation)

Data Engineer

Design and develop data pipelines:

• Design and implement scalable and efficient data integration solutions. 
• Develop and maintain data pipelines using batch and real-time processing techniques. 
• Optimize data pipelines for performance and scalability.

Support data analytics initiatives:

• Collaborate with data analysts and scientists to understand data requirements. 
• Transform business requirements into technical specifications for data pipelines. 
• Develop and maintain data models and schemas to enable efficient data analysis. 
• Implement data quality checks and data governance practices.

Ensure data quality and integrity:

• Identify and resolve data quality issues within the data ecosystem. 
• Implement data governance practices to ensure consistent, reliable, and accurate data.

Collaborate with cross-functional teams:

• Work closely with data scientists, analysts, and software engineers to understand data requirements and use cases. 
• Collaborate with database administrators and infrastructure teams to optimize data storage and processing. 
• Provide technical guidance and support to less experienced data engineers.

Strong data engineering skills:

• Expertise in designing and implementing data pipelines and workflows. 
• Demonstrated experience with batch and real-time data processing frameworks.

Data modelling and database skills:

• Solid understanding of data modelling techniques and best practices. 
• Experience with relational (e.g., MSSQL, MySQL, PostgreSQL) and NoSQL databases (e.g., Cassandra) and data warehousing concepts. 
  Programming and scripting skills: 
• Proficiency in one or more programming languages Python (or Java/ Scala). 
• Experience with scripting languages (e.g., Shell, PowerShell).

Big data technologies:

• Familiarity with distributed computing frameworks (e.g., Hadoop, Spark). 
• Experience with big data processing engines (Databricks) and query languages (Python and PySpark). 
  Data quality and governance: 
• Knowledge of data quality management principles and practices. 
• Understanding of data governance frameworks and data lineage. 
• Familiarity with metadata and data cataloging tools.

Banking domain knowledge:

• Understanding of banking products and processes (e.g., loans, deposits, payments). 
• Knowledge of regulatory requirements and compliance in the banking industry. 
  Strong analytical and problem-solving skills: 
• Ability to analyze complex data issues, identify root causes, and propose effective solutions. 
• Strong attention to detail and ability to maintain data integrity.

Communication and collaboration:

• Excellent interpersonal and communication skills. 
• Ability to work collaboratively in a cross-functional team environment. 
• Strong documentation skills.

Working at Bangkok Bank Head Office, Silom.

 For More Information, Please Contact K.Pornphun Tel. 063-212-0702