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Senior Data Engineer
Job summary
A leading data solutions provider based in Kuala Lumpur is seeking a Senior Data Engineer to join their Data and AI team. This role offers a hybrid work model and presents challenges in developing high-performance data pipelines and infrastructure. Ideal candidates have over 5 years of experience in data engineering, strong skills in Apache Spark and cloud platforms, and business-level proficiency in Mandarin for communication with teams in China. Opportunities for mentorship and collaboration with cross-functional teams are essential parts of this position.
Qualifications
- 5+ years of hands-on experience in data engineering roles, preferably within large-scale or product-based environments.
- Experience architecting and deploying data solutions on AWS, Azure, or GCP.
- Business-level proficiency in Mandarin to coordinate effectively with teams in China.
Responsibilities
- Design, build, and maintain scalable and reliable ETL pipelines for data processing.
- Architect, deploy, and optimize cloud-based data solutions for high-volume workloads.
- Mentor junior engineers and provide technical guidance.
- Collaborate closely with data scientists, engineers, and product managers.
Skills
Title: Senior Data Engineer
Location: Kuala Lumpur, Malaysia | Hybrid Work Model
Job Type: Permanent
Salary: MYR 15,000 – 18,000 per month
We are seeking an experienced Senior Data Engineer to join our growing Data and AI team in Kuala Lumpur. This role offers the opportunity to work on complex, large-scale data challenges in a fast‑evolving data‑driven environment, collaborating closely with cross‑functional teams across Engineering, Data, and Product.
As a Senior Data Engineer, you will design and implement scalable, high‑performance data pipelines and infrastructure to power data products and analytics solutions used globally. You’ll also play a key role in mentoring junior engineers and shaping best practices in data engineering.
- Data Pipeline Development: Design, build, and maintain scalable and reliable ETL pipelines for ingesting and processing data from multiple sources.
- Data Infrastructure: Architect, deploy, and optimize cloud‑based data solutions to support high‑volume and real‑time data workloads.
- System Optimization: Ensure data systems are efficient, resilient, and scalable as the organization continues to grow.
- Collaboration: Work closely with data scientists, engineers, and product managers to understand data requirements and deliver robust solutions.
- Mentorship: Provide technical guidance, mentorship, and best practices to junior engineers within the team.
- Innovation: Evaluate new data engineering tools, frameworks, and architectures to continuously improve data reliability and performance.
- Experience: 5+ years of hands‑on experience in data engineering roles, preferably within large‑scale or product‑based environments.
- Technical Skills:
- Proven expertise with distributed processing platforms such as Apache Spark, Airflow, and Hadoop.
- Strong understanding of data engineering tools and messaging systems like Kafka.
- Proficiency in Python, Java, or Scala, with solid knowledge of data structures and algorithmic complexities.
- Cloud Platforms: Experience architecting and deploying data solutions on AWS, Azure, or GCP.
- Communication: Excellent communication and collaboration skills with the ability to engage stakeholders across technical and non‑technical functions.
- Language Requirement: Business‑level proficiency in Mandarin is required to coordinate effectively with technical teams in China.
- Nice to Have: Experience with modern data warehousing, data lakes, and real‑time analytics pipelines is highly desirable.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.