jobs in PayNet (Payments Network Malaysia)

全职 Data Engineer- Python Developer - Data Lake 工作, 薪水, PayNet (Payments Network Malaysia) 公司招聘中 - Ricebowl

Data Engineer- Python Developer - Data Lake

PayNet (Payments Network Malaysia)

Undisclosed

全职

Wilayah Persekutuan Kuala Lumpur, Malaysia

分享
保存

工作地点

  • Wilayah Persekutuan Kuala Lumpur, Malaysia Malaysia

职位描述

岗位职责

Why PayNet / Why Now
  • PayNet is operating at a scale where data reliability directly affects financial integrity and regulatory confidence
  • Transaction volumes and data complexity are increasing faster than legacy pipelines can safely support
  • Teams need production‑grade data foundations to move from insight to action without bottlenecks
  • This role exists to shape how PayNet engineers data as a long‑term capability, not a one‑off solution
  • The decisions made here set standards that multiple teams will build on for years

TL;DR
  • Own the design and reliability of critical data pipelines
  • Build scalable Python-based ETL (Extract, Transform, Load) workflows used by multiple teams
  • Decide how data quality, performance, and resilience are enforced
  • Operate across cloud platforms to support enterprise-grade data needs

Why This Role Matters
  • Data decisions across PayNet depend on reliable, well-engineered pipelines
  • This role determines how fast teams can move from data to insight
  • You influence standards for data quality, scalability, and engineering rigor
  • Your work directly impacts business outcomes and regulatory confidence

What You Will Actually Do
  • Design and build production-grade data pipelines using Python
  • Own ETL workflows end-to-end, from ingestion to consumption
  • Decide and implement data quality checks that protect data integrity
  • Optimize pipelines for performance, cost, and long-term scalability
  • Deploy and operate data solutions on cloud platforms such as AWS (Amazon Web Services), GCP (Google Cloud Platform), or Azure (Microsoft Azure)

Examples of This Role in Practice
  • Redesigning a slow-running pipeline to scale with increased transaction volume
  • Partnering with Data Scientists to productionise experimental data workflows
  • Identifying and fixing data quality issues before they impact reporting
  • Choosing the right orchestration or storage approach for a new dataset
  • Documenting data flows so teams can onboard and move faster

What Will Help You Succeed
  • Strong Python fundamentals and experience building real-world data pipelines
  • Hands-on experience with data libraries and frameworks such as Pandas, NumPy (Numerical Python), and Airflow (Apache Airflow)
  • Confidence working with SQL (Structured Query Language) and relational databases
  • Practical experience with cloud platforms such as AWS, GCP, or Azure
  • Exposure to Big Data technologies such as Hadoop (Apache Hadoop) or Spark (Apache Spark) is a plus

重要安全守则

申请工作时，切勿提供您的银行或信用卡详细资料。不要转账或完成无关的在线调查问卷。如果您发现可疑内容，请举报此招聘广告。

了解更多