Industry: Life Science (Local SME)
Location: Singapore
Employment Type: Contract - Renewable
Work Arrangement: On-site

About the Employer

Our client is a Singapore-based SME in the life science industry. As part of their digital transformation roadmap, they are building a modern data environment to enable analytics, automation, and AI-driven initiatives. This role supports the end-to-end development of their data platform and analytics capability.

Job Summary

We are hiring a Data Engineer / Data Analyst with 1-2 years of relevant experience. This role will involve approximately 50-70% data engineering work and 30% data analytics work. Ideal for candidates who enjoy building data systems, performing hands-on analytics, and want to gain exposure to AI/ML projects in the future.

Candidates with experience in Azure, Microsoft Fabric, Spark, SQL, Python, and Power BI will be prioritised. Experience with data science, machine learning, or LLM Agents is a bonus.

Key Responsibilities

Data Engineering (50-70%)

• Develop, maintain, and optimise ETL/ELT pipelines using Azure Data Factory, Microsoft Fabric, PySpark, SQL, and Python.
• Design and implement data ingestion, transformation, and integration processes across multiple data sources within the life science environment.
• Build reusable data assets, structured datasets, and data models to support downstream analytics and reporting.
• Develop and maintain data lake and/or data warehouse structures following best practices.
• Implement data governance standards including data validation, data cleaning, lineage tracking, and metadata documentation.
• Monitor data pipeline performance and ensure reliability, accuracy, and completeness of datasets.
• Support the setup and enhancement of the organisation's data infrastructure to enable future AI and advanced analytics initiatives.

Data Analytics (30%)

• Conduct exploratory data analysis (EDA) to identify trends, patterns, and insights.
• Clean, transform, and prepare datasets for reporting and analysis.
• Build dashboards, automated reports, and analytical visualisations using Power BI for business users and management.
• Collaborate closely with internal stakeholders to understand business questions and translate them into data-driven solutions.
• Perform ad-hoc analysis to support operational, customer, and financial decision-making.

AI / Machine Learning (Nice-to-Have)

• Assist in early-stage prototyping of AI/ML models such as forecasting, classification, clustering, or NLP.
• Exposure to LLM agents, RAG (Retrieval-Augmented Generation), or model integration workflows is a strong bonus.
• Support data preparation and feature engineering for machine learning use cases.

Requirements

Minimum Qualifications

• Diploma or Degree in Computer Science, Information Systems, Data Science, Engineering, or related fields.
• 1-2 years of hands-on experience in Data Engineering, Data Analytics, or related roles.

Technical Skills

• Hands-on experience with Azure or Microsoft Fabric environments.
• Proficiency in SQL for data manipulation, transformation, and optimisation.
• Strong knowledge of Python for scripting, data processing, or pipeline development.
• Experience working with Spark / PySpark is preferred.
• Ability to develop dashboards and reports using Power BI.
• Understanding of data modelling concepts (star schema, snowflake, normalization).
• Familiarity with ETL/ELT pipelines, workflow automation, and data quality processes.

Soft Skills

• Strong analytical and problem-solving ability.
• Able to communicate technical concepts effectively to non-technical stakeholders.
• Able to work independently and in small teams within a fast-evolving environment.
• Willingness to learn new technologies and support digital transformation initiatives.

Work Environment & Benefits

• Competitive salary package aligned with industry standards and based on skills and experience.
• Opportunities for upskilling in AI, machine learning, and modern data platforms.
• Stable and supportive SME environment with direct impact on the organisation's transformation journey.
• Professional development opportunities as digital projects scale.

EA License No: 23C1703

EA Personnel No: R1762582

EA Personnel Name: Wong Choo Sian