Senor Data Engineer || 4-6 Years || Malaysia (KL) || 12 M Contract || Hybrid || Quick Joiners ||

We are seeking a skilled and proactive

Senior Data Engineer

to design, develop, and optimize our modern cloud-native data warehouse on AWS. This role focuses on building scalable, secure, and high-performance data pipelines that support analytics, reporting, and Al use cases across the organization. The ideal candidate is technically hands-on, solutions-oriented, and experienced in cloud-based data engineering.

Senor Data Engineer || 4-6 Years || Malaysia (KL) || 12 M Contract || Hybrid || Quick Joiners ||

Department : Transformation & Digital

Division : Analytics and Business Insights

Reporting Line : Lead of Data Engineer

Key Duties & Responsibilities :

1. Own it

Design and implement scalable data architecture

using A

WS services such as S3, Glue, Redshift, Lambda, and Step Functions.

Build and maintain robust

ETL / ELT pipelines

to transform

raw data into clean, structured datasets.

Ensure data solutions are reliable, high-performing, and production-ready.

2. Build Trust

Ensure strong data governance, security, and quality control across all pipelines and datasets. Write clean, well-documented code and support testing, automation, and version control practices.

3. One Team

Collaborate closely with analysts, business stakeholders, and IT teams to understand data needs and deliver user-friendly data solutions.

Contribute to a knowledge-sharing culture and help uplift the technical standard of the team.

4. Move Fast

Continuously refine and optimize data models (e.g., star schema) to improve reporting efficiency.

Proactively identify and address performance bottlenecks and inefficiencies in data workflows.

5 Drive Innovation

Recommend and experiment with new tools or AWS services that improve engineering efficiency and data capabilities.

Automate manual processes and drive continuous improvement in data engineering practices.

6. Delight the Customers

Build reliable datasets and pipelines that enable stakeholders to self-serve insights.

Translate business questions into data solutions that support better decision- making and improved customer outcomes.

Job Specification : Minimum

4-5 years of experience in data engineering

, with at least 2 years working in c

loud-based environments (preferably AWS).

Experience in

building and managing data models and data pipelines for large-scale data environments.

Proficiency in

AWS tools : S3, Glue, Redshift, Lambda, Step Functions. Strong SQL and Python skills for data transformation and automation.

Hands-on experience working with various data sources, including structured and unstructured data.

Solid grasp of data warehousing concepts, data modeling, and modern ELT / ETL practices. Strong problem-solving skills and ability to work independently within a cross-functional team.

Preferred  Skills :

Experience in building data warehouse for a large enterprise. Experience with Power BI, Snowflake on AWS, or Databricks.

Familiarity with DevOps practices such as CI / CD.

Understanding of AWS-based data security and governance

Strictly, prefer applicants within 0-30 days NP only

Apply Here.