Data Engineering Manager

Eames Consulting; Singapore; On-site; SGD 140,000 - 210,000; Full time

Job summary

Eames Consulting is partnering with an established firm to hire a Data Engineering Manager to lead a high-calibre data team and drive modern data platforms.

The role focuses on cloud lakehouse architectures, governance, and scalable pipelines, with strong emphasis on performance, cost efficiency, and business impact. You will mentor engineers and set strategic direction to deliver measurable outcomes.

Qualifications

• Bachelor's or Master's degree in CS or STEM.
• 5+ years of engineering people management or technical leadership.
• 10+ years building scalable distributed data systems and software.
• Hands-on knowledge of cloud data engineering, lakehouse storage, Airflow, and dbt.
• Experience with automated testing, IaC, streaming/batch ingestion, governance.
• Understanding FinOps and translating architecture to business impact.

Responsibilities

• Provide leadership, mentoring, and technical direction to a data engineering team while promoting CI/CD and observability.
• Architect and scale a cloud-based data lakehouse and transformation framework handling high-volume events and revenue streams.
• Direct migrations from legacy data setups to modern distributed storage and compute with zero business disruption.
• Embed data governance, cataloguing, lineage, and GDPR/privacy controls into data pipelines.

Skills

People management

Data engineering

Cloud data engineering

Airflow

dbt

CI/CD

Observability

FinOps

Education

Bachelor's degree in CS or STEM

Master's degree preferred

Tools

dbt

Cloud platforms (AWS/GCP/Azure)

CI/CD tooling

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.