Career
Head of Data Engineer
Technology
|
Permanent
Technology
Permanent
About Us
Do you want to be part of Thailand banking transformation? Data is the core of the new financial services era, and we are open for the opportunity to be part to drive this change at the core.
SCB DATAx is a new venture of the Siam Commercial Bank (SCB) holdings, a leading financial services and digital services holdings in Thailand and ASEAN.
As part of the transformation of SCB into a group of product and technology companies, under the SCBx brand, SCB DATAx is the technology company to centralize data and provides AI and data science services and products to the group.
With a leading-edge cloud native data & AI platform, our vision is to support the group to providing everyone in our region with the opportunity to prosper.
We work on forward-thinking challenges of centralizing, analyzing and sharing information. We collaborate with companies and experts in many different domains, embrace diversity and all that while having a good laugh and joy in work.
Discover job openings on our career page. To apply, email with the role's title as the subject, attach your CV, and specify your contact information. We're eager to learn more about you.
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Benefits
Other
Preferred Qualifications
Qualifications
Education: Bachelor’s, Master’s or Doctorate degree in Computer Science, Computer Engineering, Data Science, or a related field.
Experience: Extensive experience in data engineering, with a proven track record of managing teams and projects.
Technical Skills: Proficiency in programming languages (e.g., Python, SQL), data modeling, and familiarity with big data technologies (e.g., Hadoop, Spark).
Leadership Skills: Strong leadership and communication skills to effectively manage teams and collaborate with other departments.
Responsibilities
Leadership: Lead and manage the data engineering team, fostering a culture of innovation and collaboration.
Strategy Development: Define and implement the data engineering strategy aligned with the company’s goals.
Data Architecture: Design and oversee the architecture of data systems, ensuring scalability and reliability.
Pipeline Development: Build and maintain robust data pipelines for processing structured and unstructured data.
Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand data needs and deliver solutions.
Quality Assurance: Ensure data quality and governance standards are met across all data initiatives.
Technology Evaluation: Stay updated on emerging technologies and assess their potential impact on data engineering practices.