Senior Data Engineer

Housing and Development Board; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Housing & Development Board (HDB) is pursuing a data-driven platform to enhance policy, service delivery, and operations. We seek an experienced Data Systems Architect to design scalable cloud data architectures and lead Data Lakehouse initiatives.

You will collaborate with stakeholders, build ETL/ELT pipelines, oversee multi-cloud migrations, implement data quality checks, and mentor junior engineers while ensuring security and governance.

Qualifications

• Bachelor’s degree in computer science, IT, computer engineering, or related field.
• Minimum 3 years of experience in data systems architecture and production data pipelines.
• Strong knowledge cloud computing, IaC, containerisation, microservices, IAM, and security.
• Proven ability to translate business requirements into technical solutions.
• Excellent communication for diverse audiences.
• Experience with cloud security frameworks and data governance.
• Experience in DataOps, Data Lakehouse and AI/ML domains.

Responsibilities

• Design scalable data architectures on cloud platforms with high availability and security.
• Lead development of Data Lakehouse solutions.
• Build and maintain robust ETL/ELT pipelines using modern tools.
• Optimize data processing workflows for performance and cost.
• Implement automated data quality checks and monitoring.
• Mentor junior data engineers and participate in architecture reviews.

Skills

SQL

Python

Spark

Kafka

Airflow

Terraform

Cloud security

IAM

Distributed systems

Data Lakehouse

Education

Bachelor's degree in CS/IT/Engineering

Tools

Cloud platforms

Terraform

Job description

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:

• Data Pipeline Infrastructure & Architecture: Design and implement scalable data architectures on cloud data platforms with high availability, security, and performance.
• Lead development of Data Lakehouse solutions.
• Collaborate with stakeholders to understand requirements and translate them into technical specifications.
• Pipeline Development & Optimisation: Build and maintain robust ETL/ELT pipelines using modern data engineering tools and frameworks.
• Optimise data processing workflows for performance, cost‑effectiveness, and reliability.
• Implement automated data quality checks and monitoring systems to ensure data integrity.
• Data Systems Architecting & Solutioning: Design and architect comprehensive cloud‑native Data & AI solutions aligned with business objectives and technical requirements.
• Lead cloud migration strategies and oversee implementation of complex multi‑cloud environments.
• Drive innovation through integration of Data & AI capabilities into HDB’s Data & AI platform product architectures.
• Conduct technical assessments and recommend modernised approaches using cloud native technologies.
• Maintain architectural documentation.
• Cloud Platform Operations: Leverage Cloud Native Services to build and manage data infrastructure.
• Implement infrastructure as code practices using Terraform.
• Ensure compliance with security standards and data governance policies.
• Technical Leadership & Collaboration: Mentor junior data engineers and provide technical guidance on complex challenges.
• Participate in architectural reviews and contribute to data strategy evolution.

What we are looking for:

• Bachelor’s degree in computer science, Information Technology, Computer Engineering, or related field.
• Minimum 3 years of relevant experience in data systems architecture, data systems integration, and data pipeline setup at production scale.
• 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.
• Proven ability to translate business requirements into technical solutions.
• Excellent communication skills for presenting complex concepts to diverse audiences.
• Experience with cloud security frameworks, compliance requirements, and risk management.
• Experience in data domains (e.g. DataOps, Data Lakehouse) and AI/ML Domains (e.g. MLOps, LLMOps).
• Strong knowledge and hands‑on experience with SQL, Python and Apache Spark.
• Hands‑on experience with Apache Kafka, Airflow, or similar technologies.
• Good to Have:

• Proficiency in Amazon Web Services (AWS) services.
• Relevant cloud certifications (e.g. AWS Solutions Architect Professional, AWS Data Engineer Associate) would be an advantage.
• 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, Amazon Comprehend, Amazon Rekognition and Amazon Textract).
• Familiarity with serverless computing, edge computing, and IoT architectures.
• Experience with machine learning operations (MLOps) and ML model deployment pipelines.
• Knowledge of data governance frameworks and metadata management tools.
• Familiarity with data visualisation tools and business intelligence platforms.

Benefits and Terms:

Successful candidates will be offered a 1+1 year contract in the first instance. Conversion to permanent is dependent on good performance.