Lead Data Engineer

Lead Data Engineer

Monroe Consulting Group's Technology Division

is recruiting on behalf of a highly established

Government-Linked Company (GLC)

with a robust footprint in the

consumer, logistics, and technology

sectors. Our client is recognised for driving transformative initiatives, embracing innovation, and delivering long-term value to stakeholders. Job Summary

We are seeking an experienced and driven

Lead Data Engineer

to spearhead the design and development of a

modern, cloud-native data warehouse on AWS . This role is critical to building a scalable, secure, and efficient data platform that supports analytics, reporting, and AI use cases across the organization. The ideal candidate is both technically hands-on and capable of leading a team to deliver enterprise-grade data solutions. Job Responsibilities

Cloud Data Architecture Ownership

• Take end-to-end ownership of cloud data architecture-designing, developing, and implementing a robust data warehouse using AWS services such as S3, Glue, Redshift, Lambda, Step Functions, and Athena. Infrastructure Evolution
• Lead the evolution of data infrastructure with a long-term vision, ensuring scalability, reliability, and performance to support growing business needs. Engineering Excellence
• Define and enforce high standards across data engineering-driving excellence in source control, automation, testing, and deployment through clean, well-documented code and strong CI / CD workflows. Data Governance & Security
• Ensure data integrity, governance, and security are embedded throughout the pipeline, delivering datasets stakeholders can depend on with confidence. Technical Mentorship
• Act as a trusted technical mentor, growing the skillset of your team and raising the bar on data engineering quality through peer reviews and knowledge sharing. ETL / ELT Pipeline Development
• Design and maintain high-performance ETL / ELT pipelines to rapidly transform raw data into ready-to-use, structured datasets. Data Modeling Optimization
• Continuously optimize data models (e.g., star schema) for analytics and reporting, accelerating decision-making across the business. Agile Innovation
• Embrace agility-identify inefficiencies, ship improvements quickly, and iterate with speed and precision to drive continuous enhancement. Cross-Functional Collaboration
• Partner closely with analytics, business, and IT teams to understand needs and co-create scalable, user-friendly data solutions. Break down silos and foster a collaborative, cross-functional approach to solving complex data challenges. Inclusive Leadership
• Lead with empathy and clarity-creating an inclusive team culture where knowledge is shared and everyone is set up to succeed. Self-Service Enablement
• Build data systems that empower internal stakeholders to self-serve insights and deliver exceptional customer experiences. Innovation & Technology Leadership
• Stay ahead of the curve on emerging AWS technologies, recommending innovations that help better serve customers and scale smarter. Translate complex data into actionable solutions that directly impact product, strategy, and customer satisfaction. Key Requirements

Experience

Advanced Platforms

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