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Jobs in Singapore   »   Jobs in Singapore   »   Information Technology Job   »   Data Engineer (AI)
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Data Engineer (AI)

Bioquest Advisory Pte. Ltd.

Bioquest Advisory Pte. Ltd. company logo

We are looking for a skilled Data Engineer with strong development skills to join our dynamic consulting team. In this role, you will play a key part in designing and building scalable, high-performance data pipelines and applications, while working closely with clients to understand their unique data needs and deliver tailored solutions.


This position requires a solid foundation in data preparation, backend development, and API integration, with a primary focus on Python and React.js for frontend. You will be involved in all phases of the data lifecycle, providing technical leadership, and ensuring successful project delivery through close collaboration with clients.


Key Responsibilities:

· Client Interaction: Lead client interactions, including requirement gathering, technical discussions, and workshops to clearly define project goals and data solutions.


· Data Pipeline Development: Design, develop, and maintain robust data pipelines to process, cleanse, and transform large datasets for various applications.


· Full-Stack Development: Build secure, scalable APIs and integrate third-party services, databases (SQL, NoSQL), and systems while contributing to the development of user interfaces using React.js.


· API Integration: Develop and integrate APIs for seamless data flow between systems, ensuring high performance and security.


· Data Preparation & Processing: Implement data preparation techniques to clean, organize, and structure raw data for analysis, ensuring data readiness for machine learning and AI applications.


· Emerging Technologies: Explore and gain hands-on experience with emerging technologies such as Large Language Models (LLM) and Retrieval-Augmented Generation (RAG).


· Cross-Functional Collaboration: Collaborate with cross-functional teams to deliver high-quality projects within agreed timelines, ensuring optimal data performance and security.


· Continuous Improvement: Stay updated with the latest industry trends and technologies to drive innovation in data engineering projects.


Requirements:


· Passion for Emerging Technologies: A strong interest in staying ahead of the curve with new technologies like Large Language Models (LLM) and Retrieval-Augmented Generation (RAG), with a desire to continuously learn and integrate these into client data solutions.


· Data Engineering Expertise: Minimum of 3 years of experience in data engineering, with a strong focus on Python for backend data processing and React.js for frontend interface development.


· API Development and Integration: Expertise in building and integrating RESTful APIs for data flow and system integration, with experience working with SQL and NoSQL databases.


· Data Preparation Skills: Strong understanding of data preparation, ETL processes, and transforming unstructured or semi-structured data into structured formats.


· Infrastructure and Cloud Knowledge: Solid understanding of infrastructure, cloud platforms (Azure, AWS, GCP, Alibaba Cloud), and familiarity with network and security best practices.


· Consulting Experience: Ability to engage with clients through requirement gathering, leading workshops, and providing technical solutions that align with their data-driven business needs.


· Agile and Version Control Skills: Familiarity with agile methodologies and version control systems like Git, ensuring smooth collaboration and project efficiency.


· Problem Solving & Communication: Strong problem-solving skills with the ability to communicate complex technical information effectively to both technical teams and non-technical clients.


· Client-Focused Approach: Ability to understand client needs and translate them into scalable, high-performance data solutions that deliver value and enhance user experience.


· Track Record: Proven experience leading technical projects, guiding the data development lifecycle from requirements gathering to deployment, while ensuring quality and client satisfaction.

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