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Employment Type: Contract (12 Months, Renewable)
Eligibility: This opportunity is currently open to Malaysian Citizens
About the Role
We are seeking an experienced Principal Data Engineer to provide technical leadership in designing, building, and operationalizing enterprise-scale data platforms. The successful candidate will lead the development of cloud-native data pipelines, scalable data models, and reusable engineering frameworks while ensuring production reliability and enabling trusted, self-service analytics across the organization.
This is a hands‑on technical leadership role requiring strong expertise in cloud data engineering, architecture, DataOps, and mentoring engineering teams.
Key Responsibilities
- Lead the design, development, and delivery of enterprise data engineering solutions.
- Design and maintain scalable data pipelines, curated datasets, and reusable engineering frameworks.
- Drive technical excellence across data ingestion, transformation, modeling, and operational support.
- Ensure production stability through monitoring, incident management, root cause analysis, and continuous improvement.
- Develop engineering standards, coding best practices, automation, and reusable components.
- Collaborate with Data Architects, Platform Engineers, BI teams, Data Scientists, and business stakeholders to deliver trusted data solutions.
- Implement automated data quality validation, reconciliation, and monitoring processes.
- Lead design reviews, code reviews, and mentor Data Engineers on engineering best practices.
- Support cloud-native DataOps practices, CI/CD implementation, and production deployments.
- Prepare technical documentation, architecture diagrams, and engineering standards.
Requirements
- Bachelor's Degree in Computer Science, Information Technology, Data Engineering, or a related discipline.
- 7–10+ years of experience in Data Engineering, including strong experience designing enterprise cloud-native data platforms.
- Proven experience leading complex data engineering initiatives from design through production support.
- Strong technical leadership experience through architecture reviews, mentoring, and engineering governance.
- Excellent analytical, communication, and stakeholder management skills.
Technical SkillsCloud & Data Platforms
- Snowflake
- AWS SageMaker
- Python
- SQL
- ETL / ELT Development
- Data Modeling
AWS Services
- Amazon S3
- AWS Lambda
- AWS CloudWatch
- AWS KMS
- AWS Transfer Family
- Workflow Orchestration
- Data Transformation
- Data Quality Validation
- CI/CD
- Performance Optimization
- Monitoring & Observability
- Production Support
- Medallion Architecture (Bronze, Silver, Gold)
- Data Lake
- Data Warehouse
- Self-Service Analytics
Preferred Skills
- Experience with Snowflake Streams, Tasks, Stored Procedures, UDFs, RBAC, Cortex AI, and Streamlit.
- Strong knowledge of Apache Airflow DAG design, orchestration, dependency management, and scheduling.
- Experience with Airbyte, Fivetran, or similar ELT frameworks.
- Familiarity with Machine Learning and AI integration using cloud platforms.
- Experience implementing enterprise data governance and automated data quality controls.
- Strong understanding of DataOps and cloud-native engineering practices.
Why Join Us?
- Opportunity to lead enterprise-scale cloud data engineering initiatives.
- Work with modern cloud technologies including AWS, Snowflake, Airflow, and AI-driven data platforms.
- Collaborative environment focused on technical excellence and innovation.
- Competitive remuneration with opportunities for contract renewal and career growth.
We thank all applicants for their interest. Only shortlisted candidates will be contacted.