Senior Data Engineer

michael page (personnel) pte. ltd.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Our client, a technology-driven enterprise in Singapore, is undergoing a data and AI transformation to build a modern data foundation enabling business decisions, efficiency, and innovation at scale.

As a Senior Data Engineer, you will design and deliver reliable, scalable data platforms that support BI, analytics and AI initiatives. You will work with data engineers, scientists, and analytics teams to implement robust data layers and governance.

Qualifications

• Bachelor's or master's degree in Computer Science, Information Systems, Data Engineering, or related discipline.
• Experience in data engineering, data platform development, or large-scale data infrastructure environments.
• Strong SQL and Python, with experience in Spark, Hadoop, dbt, and Airflow.
• Experience designing and supporting enterprise-level cloud data platforms and large-scale datasets.
• Exposure to Databricks and Snowflake.
• Knowledge of MLOps frameworks and tools such as SageMaker or MLflow.

Responsibilities

• Design, develop, and maintain scalable data pipelines for ingestion, transformation, and delivery across multiple domains.
• Build and automate ETL/ELT workflows using orchestration and cloud technologies for reliability and efficiency.
• Optimize data lakehouse and warehouse environments for performance and cost.
• Collaborate with Data Scientists and Analytics teams to support ML/AI initiatives.
• Implement data quality, governance, and security controls across the data stack.
• Enable CI/CD, IaC, and containerized deployment practices.
• Drive continuous improvements through architectural enhancements and automation.

Skills

SQL

Python

Spark

Airflow

dbt

Education

Bachelor's or Master's in CS/Data/IS

Tools

Databricks

Snowflake

AWS (Redshift, Glue, S3, Athena, EMR, Lambda)

Job description

• Design enterprise-scale data platforms powering analytics and AI
• Lead automation, MLOps, and cloud data transformation initiatives

About Our Client

Our client is a technology-driven enterprise undergoing a significant data and AI transformation journey. With a strong focus on leveraging cloud platforms, advanced analytics, and machine learning, the organization is building a modern data foundation that empowers business decision-making, operational efficiency, and innovation at scale. The company offers a collaborative environment where data engineering, analytics, and AI teams work closely to deliver measurable business outcomes while embracing engineering excellence and continuous improvement.

Job Description

As a Senior Data Engineer, you will play a critical role in designing and delivering reliable, scalable, and production-grade data platforms that support business intelligence, advanced analytics, and AI initiatives.

• Design, develop, and maintain scalable data pipelines for ingestion, transformation, and delivery across multiple business domains.
• Build and automate ETL/ELT workflows using modern orchestration and cloud technologies to improve reliability and efficiency.
• Optimize enterprise data lakehouse and warehouse environments, ensuring performance, scalability, and cost effectiveness.
• Partner with Data Scientists and Analytics teams to build robust data foundations that support machine learning and AI solutions.
• Implement data quality frameworks, monitoring solutions, governance standards, and security controls across the data ecosystem.
• Enable CI/CD practices, Infrastructure-as-Code, and containerized deployment methodologies to support modern engineering standards.
• Drive continuous improvement initiatives through technology evaluation, architecture enhancements, and automation best practices.

The Successful Applicant

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related discipline.
• Experience in data engineering, data platform development, or large-scale data infrastructure environments.
• Strong proficiency in SQL and Python, with hands-on experience in data processing frameworks such as Spark, Hadoop, dbt, and Airflow.
• Proven expertise designing and supporting enterprise-level cloud data platforms and large-scale datasets.
• Experience with AWS data services including Redshift, Glue, S3, Athena, EMR, Lambda, and Lake Formation.
• Exposure to modern cloud analytics platforms such as Databricks and Snowflake.
• Knowledge of MLOps frameworks and tools including SageMaker, MLflow, or similar machine learning deployment platforms.
• Strong understanding of data governance, security, compliance, and data quality management practices.
• Professional certifications in cloud, data engineering, or solution architecture will be advantageous

What's on Offer

• Opportunity to shape and scale a next-generation enterprise data and AI platform.
• Exposure to cutting-edge cloud, analytics, and machine learning technologies.
• High-impact role working alongside experienced data, analytics, and engineering professionals.
• Strong emphasis on innovation, automation, and technical excellence.
• Continuous learning and professional development opportunities.
• Career progression within a growing data and digital transformation environment.
• Collaborative culture with visibility across senior business and technology stakeholders.