Data Engineer
Data Engineer at Mettler-Toledo in Petaling Jaya, Malaysia who designs, builds and maintains the company's central data platform — developing scalable batch/streaming pipelines, ETL/ELT flows, and the enterprise data lake/lakehouse using Databricks, Snowflake and Python/SQL to power analytics and AI/ML initiatives.
- Compensation
- Not disclosed
- Location
- Petaling Jaya, Malaysia
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent technical field
- 3+ years of hands-on experience in data engineering or a similar role
- Strong experience with data processing frameworks: Apache Spark, Snowflake, Databricks
- Programming languages: Python, SQL
- Solid understanding of data modeling, ETL/ELT, and data warehousing principles
- Experience with orchestration tools (e.g., Airflow, Prefect)
- Familiarity with cloud platforms
- Experience with metadata management tools
- Strong analytical and problem solving skills
- Ability to work collaboratively in a cross-functional environment
- Good communication and documentation skills
- Commitment to high-quality work, data security, and continuous improvement
Nice to have
- Cloud platform experience with Azure
Full description
METTLER TOLEDO is a global leader in precision instruments and services. We are renowned for innovation and quality across laboratory, process analytics, industrial, product inspection, and retailing applications. Our sales and service network is one of the most extensive in the industry. Our products are sold in more than 140 countries, and we have a direct presence in approximately 40 countries. For more information, please visit www.mt.com.
Our Opening and Your Responsibilities
The Data Engineer will design, build and maintain METTLER TOLEDO’s central data platform supporting analytics, data distribution and AI/ML initiatives. This role involves developing scalable data pipelines, ensuring high-quality and secure data flows, and contributing to the foundation that powers advanced analytics and business insights across the organization.
The person on this position will work closely with data scientists, analysts, and business stakeholders to design, build, deliver and support trusted, well-structured and secure high-quality data for operational, analytical and AI/ML use cases.
Contribute to the development of the enterprise data lake/lakehouse using modern technologies (Databricks, Snowflake).
Build and maintain data integration pipelines for batch and streaming data between internal systems, external partners and cloud services.
Implement ETL/ELT and reverse ETL processes to support analytics, reporting and AI/ML workloads.
Develop, optimize, and maintain scalable data pipelines for structured, semi structured, and unstructured data.
Monitor, troubleshoot, support and resolve any issues with data pipelines and data availability.
Automate ingestion, transformation, and distribution workflows using orchestration tools.
Create and maintain metadata catalogs, data lineage and feature stores.
Collaborate closely with cross-functional teams and business stakeholders to understand data requirements and deliver efficient technical solutions.
Evaluate and adopt new tools and technologies to improve platform performance, cost management and engineering practices.
Follow best-in-class development, testing, and documentation standards, especially also using CI/CD pipelines.
Apply and maintain data quality rules ensuring accuracy, completeness, and consistency across pipelines.
Ensure adherence to security, compliance, and data protection standards.
What You Need to Succeed
Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent technical field.
3+ years of hands-on experience in data engineering or a similar role.