Data Engineer( Snowflake, ETL/ELT ) (Weekends,shifts)– Contract #IKR

Recruit Express Pte Ltd; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Recruit Express Pte Ltd is seeking a skilled data engineer to design and operate production-grade data pipelines in a cloud-native Snowflake environment. You will own end-to-end data flows from ingestion to distribution and collaborate with business stakeholders to translate requirements into scalable data models.

You will maintain data platforms, optimize performance and cost, automate quality checks, and drive governance and DevOps practices to accelerate analytics and trustworthy data

Qualifications

• Experience: 3–6 years hands-on data engineering in production cloud environments.
• Snowflake Architecture Expertise: deep knowledge of Snowflake components (virtual warehouses, databases, schemas, Snowpark, Streams, Tasks).
• ETL/ELT Proficiency: expert SQL and complex ETL/ELT pipelines in cloud ecosystems.
• Data Fundamentals: data modeling, data quality validation, and modern DevOps CI/CD practices.

Responsibilities

• Pipeline Engineering: Design, build, and deploy scalable data ingestion, transformation, and distribution pipelines within Snowflake.
• Data Platform Maintenance: Construct and maintain data platforms, centralized datasets, and reusable data products with governance.
• Performance & Cost Optimization: Tune data service performance, availability, and operational cost efficiency with observability.
• Automation & Quality Control: Automate data operations, quality frameworks, verification checks, and data lineage.
• Business Analytics Support: Translate business requirements into trusted data models and decision-support systems.
• Stakeholder Management: Collaborate with cross-functional stakeholders to align on information requirements and communicate trade-offs.
• Process Modernization: Drive engineering efficiency by reusable design patterns and AI coding tool integrations into workflows.

Job description

Job Description

• Pipeline Engineering: Design, build, and deploy highly scalable data ingestion, transformation, and distribution pipelines within the cloud-native Snowflake ecosystem.
• Data Platform Maintenance: Construct and maintain robust data platforms, centralized datasets, and reusable data products in strict accordance with platform governance and engineering best practices.
• Performance & Cost Optimization: Continuous tuning of data service performance, service availability, operational cost efficiency, and end-to-end data observability.
• Automation & Quality Control: Automate data operations, quality frameworks, and verification checks to guarantee data lineage, integrity, and organizational trust.
• Business Analytics Support: Translate complex business requirements into trusted data models and decision-support systems, taking complete end-to-end ownership of project deliverables.
• Stakeholder Management: Partner actively with cross-functional business and technical stakeholders to align on information requirements while clearly communicating technical architecture trade-offs.
• Process Modernization: Drive engineering efficiency across the data lifecycle by pioneering reusable design patterns and integrating cutting-edge AI coding tools (e.g., GitHub Copilot, Cursor) into workflows.

Requirements

• Experience: Minimum 3 to 6 years of hands-on data engineering experience, with a core focus on production-scale cloud environments.
• Snowflake Architecture Expertise: Deep practical knowledge of Snowflake core components, including virtual warehouses, database/schema structures, and advanced features such as Snowpark, Streams, and Tasks.
• ETL/ELT Proficiency: Expert-level mastery of SQL and extensive experience developing complex ETL/ELT pipelines in modern cloud ecosystems.
• Data Fundamentals: Minimum 2+ years of solid experience in data modeling methodologies, data quality validation frameworks, and modern DevOps CI/CD practices.