Data Engineer - Iceberg/Snowflake

VUI SYSTEMS PTE. LTD.; Singapore; On-site; SGD 90,000 - 180,000; Full time

Job summary

VUI SYSTEMS PTE. LTD. seeks an experienced Data Engineer to design, build, and optimize scalable data pipelines and lakehouse architectures. You will implement end-to-end ETL/ELT processes using Python and SQL, and manage Snowflake data warehousing for analytics.

The role includes creating a dedicated China data environment on Alibaba Cloud and ensuring data quality, performance, and reliability across data platforms. Collaboration with stakeholders is essential.

Qualifications

• Bachelor's degree in a relevant field required.
• Minimum 5+ years in Data Engineering, Data Warehousing, or Big Data environments.
• Strong hands-on experience with Apache Iceberg and Snowflake for data warehousing and analytics.
• Advanced proficiency in Python and SQL development.
• Experience designing and building ETL/ELT pipelines and data integration solutions.
• Solid understanding of data lake, lakehouse, and data warehouse architectures.

Responsibilities

• Design, develop, and implement scalable data engineering solutions to support program requirements.
• Build and maintain ETL/ELT pipelines using Python, SQL, and modern data engineering frameworks.
• Develop and manage data lakehouse architectures using Apache Iceberg and Snowflake.
• Create and support China data environment on Alibaba Cloud for data processing, analytics, and reporting workloads.
• Automate data ingestion, transformation, validation, and reporting processes to improve efficiency.

Skills

Apache Iceberg

Snowflake

Python

SQL

ETL/ELT Development

Data Engineering

AlibabaCloud (preferred)

Data Lakehouse Architecture

Education

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline

Tools

AWS services

IAM

S3

CloudWatch

Monitoring

Job description

JobResponsibilities

• Design, develop, and implement scalable data engineering solutions to support PIPL program requirements.
• Build and maintain end-to-end ETL/ELT pipelines using Python, SQL, and modern data engineering frameworks.
• Develop and manage data lakehouse architectures using Apache Iceberg and Snowflake.
• Create and support a dedicated China data environment on Alibaba Cloud (AliCloud) for data processing, analytics, machine learning, and reporting workloads.
• Automate data ingestion, transformation, validation, and reporting processes to improve operational efficiency.
• Optimize data pipelines, storage, and query performance to ensure scalability and reliability.
• Collaborate with architects, program leads, and business stakeholders to gather requirements and deliver data solutions.
• Monitor, troubleshoot, and resolve data platform and pipeline issues.
• Contribute to best practices in DataOps, CI/CD, automation

JobRequirements

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline.
• 5+ years of experience in Data Engineering, Data Warehousing, or Big Data environments.
• Strong hands-on experience with Apache Iceberg.
• Proven experience working with Snowflake for datawarehousing and analytics.
• Advanced proficiency in Python and SQL development.
• Experience designing and building ETL/ELT pipelines and data integration solutions.
• Solid understanding of data lake, lakehouse, and data warehouse architectures.
• Experience working with cloud platforms, preferably Alibaba Cloud (AliCloud).
• Knowledge of distributed data processing technologies such as Apache Spark, Flink, or similar frameworks.
• Experience with data modeling, performance tuning, and data quality management.
• Familiarity with CI/CD pipelines, Git, and automation tools.
• Strong analytical, problem-solving, and stakeholder management skills.
• Experience in regulatory or data privacy-focused environments(PIPL/GDPR) is an added advantage.

Must-HaveSkills:

Apache Iceberg, Snowflake, Python, SQL, ETL/ELT Development, Data Engineering, AlibabaCloud (preferred), Data Lakehouse Architecture.

• Good understanding of AWS services, data lakes, IAM, S3,CloudWatch, and monitoring.