Data Engineering Manager

eames consulting group (singapore) pte. ltd.; Singapore; On-site; SGD 210,000 - 270,000; Full time

Job summary

eames consulting group (singapore) pte. ltd. is seeking a Data Engineering Manager to lead a high-caliber team responsible for building scalable data platforms in the cloud.

You will drive architectural decisions, ensure observability, and promote engineering best practices across the data stack. The role focuses on modern lakehouse architectures, distributed storage and compute, and governance, with emphasis on delivering reliable, cost-aware solutions while mentoring engineers and aligning

Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related STEM field.
• 5+ years of engineering people management or team leadership experience.
• 10+ years building scalable distributed data systems and software solutions.
• Hands-on knowledge of cloud data engineering, lakehouse storage, orchestration tools, and data transformation engines.
• Experience with automated testing, infrastructure-as-code, streaming/batch ingestion, and governance frameworks.
• Understanding FinOps and translating architecture into business impact.

Responsibilities

• Provide leadership, mentoring, and technical direction to a data engineering team.
• Design and scale cloud-based data lakehouse architectures for high-volume events.
• Oversee migrations from legacy data setups to modern distributed storage and compute.
• Embed data governance, lineage tracking, and GDPR/privacy controls into pipelines.

Skills

People management

Cloud data engineering

Data lakehouse

CI/CD

Data governance

Education

Bachelor’s or Master’s degree in Computer Science or a relevant STEM discipline

Tools

Airflow

dbt

Cloud platforms (AWS/GCP/Azure)

Job 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.