Data & Machine Learning Engineering Lead

ofi; Singapore; On-site; SGD 100,000 - 140,000; Full time

Job summary

A global leader in food & beverage ingredients is seeking a Data & Machine Learning Engineering Lead in Singapore. The role involves leading an engineering team, managing data infrastructure, and driving innovation through data-driven solutions. Ideal candidates should have over 8 years of experience, including proficiency in ETL processes and knowledge of the Snowflake ecosystem. A collaborative mindset and strong problem-solving skills are essential.

Qualifications

• 8+ years of proven experience in data engineering, with at least 2 years in a Data Engineering Lead role.
• Proficiency in data pipeline tools, particularly within the Snowflake ecosystem.
• Extensive experience with SQL databases and multiple programming languages.

Responsibilities

• Lead the engineering team and manage data infrastructure.
• Design sustainable ETL processes and workflows for evolving data platforms.
• Implement data governance and security systems.

Skills

Problem-solving

Collaboration

People leading

Education

Bachelor's or master's degree in Computer Science, Data Analytics, Data Science, Information Technology, or related fields

Tools

Python

SQL

Docker

Kubernetes

Azure

Snowflake

Informatica

Job description

Data & Machine Learning Engineering Lead

Job Description:You will be joining a global leader in food & beverage ingredients that is dedicated to staying ahead of consumer trends and providing exceptional products to food & beverage manufacturers. The company focuses on making a positive impact on both people and the planet by ensuring quality, reliable, and transparent supply chains. Your role as a Data & ML Engineering Lead will be crucial in driving innovation and business transformation through data-driven solutions. You will lead the engineering team, manage data infrastructure, and collaborate with various stakeholders to ensure the seamless flow and integrity of data across the organization.Key Responsibilities:- Data Engineering: - ETL: Design sustainable ETL processes and workflows for evolving data platforms. - Tooling: Utilize technologies like Python, SQL, Docker, Kubernetes, and Azure for acquiring, ingesting, and transforming large datasets. - Infrastructure: Manage data infrastructure, including the Snowflake data warehouse, to ensure efficient access for data consumers. - Governance: Implement data governance and security systems. - Data assets: Participate in data collection, structuring, and cleaning while maintaining data quality. - Tool development: Create tools for data access, integration, modeling, and visualization. - Software development: Ensure code is maintainable, scalable, and debuggable. - Machine Learning: - Front-end integration: Design production pipelines and front-end integration for model output consumption. - Maintenance: Ensure uninterrupted execution of production tasks. - Software development: Ensure maintainability, scalability, and debuggability of data science code. - Tool development: Automate repeatable routines in ML tasks and drive performance improvements in the production environment. - Performance optimization: Identify performance improvements and select appropriate ML technologies for production. - Platform Ownership: - Platform ownership: Manage end-to-end platform ownership and stakeholder relationships. - Architecture strategy: Implement data and ML architecture aligned with business goals. - Project management: Manage resources and timelines for data engineering and model operationalization projects. Individual Skills & Mindset:- Problem-solving: Demonstrate curiosity, analytical skills, and a strong sense of ownership.- Collaboration: Build trust and rapport to create an effective workplace and work well within an agile team.- People leading: Coach data and ML engineers and contribute to knowledge development.- Team-player: Contribute to knowledge development and the enhancement of tools and code base.Qualifications:- Bachelor's or master's degree in Computer Science, Data Analytics, Data Science, Information Technology, or related fields.- 8+ years of proven experience in data engineering, with at least 2 years in a Data Engineering Lead role.- Proficiency in data pipeline tools, particularly within the Snowflake ecosystem.- Extensive experience with SQL databases and multiple programming languages.- Familiarity with data quality tools such as Informatica.Preferred Skills:- Knowledge of SAP ERP (S4HANA and ECC) and its integration with Snowflake.- Functional understanding of customer experience, manufacturing, supply chain, and financial concepts.Applicants are required to complete all steps in the application process, including submitting a resume/CV, to be considered for open roles.,

Sign-in & see how your skills match this job

• Data & Machine Learning Engineering Lead

Find Your perfect Job

Sign-in & Get noticed by top recruiters and get hired fast