eames consulting group (singapore) pte. ltd.
Data Engineering Manager
A people-management role leading a data engineering team in Singapore: architecting and scaling a cloud-based data lakehouse for high-volume consumer behavioural events, migrating legacy data systems, and embedding automated governance (GDPR) and CI/CD best practices. Core tech includes cloud data platforms, lakehouse storage, Airflow orchestration, and dbt transformations.
- Compensation
- Not disclosed
- Location
- Singapore, Singapore
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Bachelor's or Master's degree in Computer Science or a relevant STEM discipline
- At least 5 years of engineering people management or technical team leadership experience
- At least 10 years of overall technical background building scalable distributed data systems and robust software solutions
- Deep hands-on knowledge of cloud data engineering, lakehouse storage layers, orchestration tools (e.g., Airflow), and data transformation engines (e.g., dbt)
- Strong track record in establishing automated testing, infrastructure-as-code, streaming/batch ingestion, and governance frameworks
- Solid commercial understanding of cloud cost optimization (FinOps) and translating technical architecture into product/business impact
Full description
We are partnered with an established firm to look for a Data Engineering Manager.
Key Responsibilities
- Provide leadership, mentoring, and technical direction to a high-calibre data engineering team while fostering engineering best practices, CI/CD, and system observability.
- Lead the architectural design and scaling of a modern cloud-based data lakehouse and transformation framework processing high-volume consumer behavioural events and revenue streams.
- Direct system migrations from legacy data setups to next-generation distributed storage and compute frameworks with zero business disruption.
- Embed automated data governance, cataloguing, lineage tracking, and regulatory compliance protocols (GDPR/privacy frameworks) directly into data pipelines.
Requirements
- Bachelor’s or Master’s degree in Computer Science or a relevant STEM discipline.
- At least 5 years of engineering people management or technical team leadership experience.
- At least 10 years of overall technical background building scalable distributed data systems and robust software solutions.
- Deep hands-on knowledge of cloud data engineering, lakehouse storage layers, orchestration tools (e.g., Airflow), and data transformation engines (e.g., dbt).
- Strong track record in establishing automated testing, infrastructure-as-code, streaming/batch ingestion, and governance frameworks.
- Solid commercial understanding of cloud cost optimization (FinOps) and translating technical architecture into product/business impact.