Senior Data Engineer

[What the role is]

The mission of Housing & Development Board (HDB) is to provide affordable, quality housing and a great living environment where communities thrive. To achieve its mission, HDB aims to be data-driven to the core and adopt evidence-based decision making in developing better policies, improving service delivery, and optimising operations.

[What you will be working on]

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Data Pipeline Infrastructure & Architecture

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• Design and implement scalable data architectures on cloud data platforms with high availability, security, and performance
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• Lead development of Data Lakehouse solutions
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• Collaborate with stakeholders to understand requirements and translate them into technical specifications
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Pipeline Development & Optimisation

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• Build andmaintainrobust ETL/ELT pipelines using modern data engineering tools and frameworks
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• Optimise data processing workflows for performance, cost-effectiveness, and reliability
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• Implement automated data quality checks and monitoring systems to ensure data integrity
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Data Systems Architecting & Solutioning

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• Design and architect comprehensive cloud-native Data & AI solutions aligned with businessobjectivesand technical requirements
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• Lead cloud migration strategies and oversee implementation of complex multi-cloud environments
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• Drive innovation through integration of Data & AI capabilities into HDB’s Data & AI platform product architectures
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• Conduct technical assessments and recommend modernised approaches using cloud native technologies
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• Maintain architectural documentation
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Cloud Platform Operations

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• Leverage Cloud Native Services to build and manage data infrastructure
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• Implement infrastructure as code practices using Terraform
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• Ensure compliance with security standards and data governance policies
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Technical Leadership & Collaboration

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Mentor junior data engineers andprovidetechnical guidance on complex challenges

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Participate in architectural reviews and contribute to data strategy evolution

[What we are looking for]

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Bachelor’s degree in computer science, Information Technology, Computer Engineering, or related field

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Minimum 3 years of relevant experience in data systems architecture, data systems integration, and data pipeline setup at production scale

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Good understanding of cloud computing principles including infrastructure as code, containerisation, microservices architecture, cloud security frameworks, identity and access management, network architecture, and distributed systems

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Proven ability to translate business requirements into technical solutions

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Excellent communication skills for presenting complex concepts to diverse audiences

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Experience with cloud security frameworks, compliance requirements, and risk management

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Experience in data domains (e.g.DataOps, Data Lakehouse) and AI/ML Domains (e.g.MLOps,LLMOps)

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Strong Knowledge and Hands-on experience with SQL, Python and Apache Spark

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Hands-on experience with Apache Kafka, Airflow, or similar technologies

Good to Have

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• Proficiencyin Amazon Web Services (AWS) services
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• Relevant cloud certifications (e.g. AWS Solutions Architect Professional, AWS Data Engineer Associate) would be an advantage
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• Experience with Data & AI cloud-native services (e.g. Amazon SageMaker Unified Studio, Amazon Quick Suite, AWS S3, AWS Glue, AWS Lake Formation, AWS Bedrock, AWS Agent Core).
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• Familiarity with serverless computing, edge computing, and IoT architectureswould be an advantage.
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• Experience with machine learning operations (MLOps) and ML model deployment pipelines
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• Knowledge of data governance frameworks and metadata management tools
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• Familiarity with data visualisation tools and business intelligence platforms