Senior Principal Data Engineering Lead
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Monthly Salary:
Experience Required:
Posted on:
6 hours ago
Vacancies:
1 Vacancy
Job Summary
Role: Senior Principal Data Engineering Lead
Location: Singapore
To lead and scale the Data Engineering DataOps and Data Stewardship functions within the Data oragnization. This role ensures end-to-end delivery excellence of the cloud-native data platform spanning data ingestion transformation modeling and operations to enable reliable high-quality and self-service analytics across business domains.
Responsibilities:
- Team Leadership: Recruit mentor and lead a hybrid team of data engineers and stewards across Singapore Malaysia and India establishing in-house technical leadership and delivery ownership.
- Data Engineering Delivery: Oversee design development and optimization of ELT/ETL pipelines and data models ensuring scalable reusable and cost-efficient workflows.
- Data Quality & Stewardship: Institutionalize stewardship processes define ownership models implement DQ monitoring and drive remediation workflows with cross-functional data users.
- Operational Excellence: Manage daily pipeline operations SLA compliance and production issue resolution with strong root-cause analysis and continuous improvement.
- Technical Governance: Set engineering standards for observability RBAC cost tagging and CI/CD practices.
- Collaboration & Enablement: Enable self-service analytics by curating trusted datasets and modelled views working with BI and business teams.
Requirements
- 812 years of experience in cloud-native data engineering with strong architecture and delivery experience on AWS.
- Proven leadership of cross-functional and hybrid engineering teams including vendor-augmented resources.
- Experience partnering with BI and business teams to design modelled datasets and enable self-service analytics.
- Deep hands-on technical expertise including: Snowflake: schema design Streams/Tasks Stored Procedures UDFs RBAC performance tuning Cortex AI Streamlit cost monitoring.
- Airflow or similar data orchestration tools: orchestration scheduling dependency management and observability.
- Python and SQL: pipeline scripting transformation logic and data validation.
- ELT/ETL frameworks: Airbyte Fivetran and custom connector development.
- AWS services: S3 (data lake structures and archival) Lambda KMS Transfer Family CloudWatch Sagemaker.
- Demonstrated success delivering medallion architecture (Bronze/Silver/Gold) and enabling self-service data use cases.
- Experience building data quality frameworks stewardship policies and data lineage tracking across enterprise datasets.
- Familiarity with machine learning integration using platforms like AWS SageMaker.
- Proven ability to troubleshoot complex data issues lead root-cause analysis and ensure production stability.
- Track record of transitioning delivery ownership from vendors to internal teams while maintaining quality and velocity.
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Company Industry
IT Services and IT Consulting
Key Skills
- Tomcat
- Risk Management
- ICD Coding
- Solaris
- Solution Architecture
- PaaS
- Middleware
- Perl
- Weblogic
- Jboss
- NetSuite
- Oracle
