Principal Data Engineer

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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.