Senior Data Engineer

Housing & Development Board
Singapore, Singapore
Salary not specified
Posted
Full-time
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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). - Familiarity with serverless computing, edge computing, and IoT architectures would be an advantage. - 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

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