Data Engineer/Analyst (Junior)

WOLA RECRUITMENT PTE. LTD.; Singapore; On-site; SGD 50,000 - 70,000; Full time

Job summary

A leading recruitment agency in Singapore is seeking a Data Engineer / Data Analyst to support a digital transformation roadmap in the life science sector. This role will involve about 50-70% data engineering tasks and 30% analytics, ideal for those eager to work with AI/ML projects. Candidates with experience in Azure, SQL, and Python will be prioritized. Opportunities for professional development in AI and data platforms are offered.

Benefits

Competitive salary package

Opportunities for upskilling in AI

Professional development opportunities

Qualifications

• 1–2 years of hands-on experience in Data Engineering or Data Analytics.
• Hands-on experience with Azure or Microsoft Fabric.

Responsibilities

• Develop, maintain, and optimise ETL/ELT pipelines using Azure Data Factory.
• Conduct exploratory data analysis to identify trends.
• Clean and prepare datasets for reporting and analysis.

Skills

Azure

SQL

Python

Power BI

Spark / PySpark

Education

Diploma or Degree in Computer Science or related fields

Job description

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