Job Description

Working Hours: Monday – Thursday (8.30am –6pm), Friday (8.30am – 5.30pm) (Hybrid working arrangement)

Working Location: Central 

Salary Package: Up to $14,000 

Employment Type: 6 months contract (renewable) 

Responsibilities: 
    • Lead and implement data engineering strategy and architecture blueprints in alignment with business requirements.
    • Contribute to evaluation of data platforms and architecture solutions to support evolving data needs. E.g. Data storage / usage for AI purposes.
    • Translate business data requirements into technical specifications and scalable solutions.
    • Architect and build ingestion pipelines to collect, clean, merge, and harmonize data from diverse sources.
    • Design and implement secure, cloud-based data infrastructure and access mechanisms.
    • Monitor and optimize ETL systems and databases for performance, reliability, and scalability.
    • Construct reusable data models and maintain data catalogues with metadata and lineage using tools such as ER/Studio.
    • Collaborate with data stewards to enforce data governance, quality, and security policies.
    • Guide agencies through greenfield and brownfield implementations, from problem definition to solution design.
    • Develop standardized approaches for assessments, discovery, and solutioning
    • Champion engineering excellence and influence adoption of modern data and infrastructure practices.

Requirements: 
    • Bachelor’s degree in computer science, Software Engineering, Information Technology, or related disciplines.
    • 5-10 years of experience in data engineering, cloud infrastructure, or platform engineering.
    • Deep understanding of data system design, data structures, algorithms, and data architecture modelling.
    • Hands-on experience with cloud platforms (AWS, Azure, GCP) and distributed data technologies (Spark, Hadoop).
    • Proficiency in Python and SQL.
    • Experience with orchestration frameworks (Airflow, Azure Data Factory) and DevOps tools (Docker, Git, Terraform).
    • Familiarity with CI/CD pipelines and infrastructure-as-code practices.
    • Experience with Databricks / Snowflake / Denodo and implementing batch/real-time data pipelines.

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Wong Siew Ting (Maeve) - R25127375
ScienTec Consulting Pte Ltd - 11C5781