Data Engineer (Hybrid)

Company Overview

NCS is a leading AI Tech Services company. With a 15,000-strong team across the Asia Pacific, NCS scales its platforms and capabilities to provide clients with greater agility and AI expertise across a range of industries. Embracing a strong ecosystem of global partners, NCS transforms technology services delivery combining AI with digital resilience to drive real business impact. NCS is a subsidiary of the Singtel Group.

Capability RequirementsThe role requires strong capabilities in Snowflake data engineering, including data ingestion, transformation, distribution, data modeling, and the development of scalable data pipelines. The role requires proficiency in SQL and ETL/ELT processes, with experience in data quality, lineage, observability, CI/CD, and cloud-based data platforms. The role is expected to manage data products end-to-end, translate business requirements into reliable and trusted data solutions, and communicate effectively with technical and business stakeholders. Experience with AWS data services, software engineering practices, AI agents, and AI-assisted coding tools is an advantage.

Duties and Responsibilities

• Design, develop, and maintain scalable data ingestion, transformation, and distribution pipelines within the Snowflake ecosystem.
• Build and maintain data platforms, datasets, and reusable data products in accordance with established platform standards and engineering best practices.
• Optimize data pipeline performance, availability, cost efficiency, and observability while automating operational processes and quality controls.
• Apply data engineering practices to ensure data quality, integrity, lineage, and reliability across data platforms and solutions.
• Translate business requirements into reliable data solutions that support analysis, reporting, and decision-making, taking ownership of deliverables from development through deployment.
• Collaborate with business and technical stakeholders to understand data requirements, align solutions with business needs, and communicate technical considerations and trade-offs.
• Drive continuous improvement in data engineering practices, development efficiency, automation, and the adoption of reusable solutions and patterns.

Job Specifications

• Related Work Experience - 3–6 years of relevant experience in data engineering, including hands-on experience with Snowflake.

  • Demonstrated experience in developing and maintaining cloud-based data pipelines and ETL/ELT processes.
  • At least 2 years of experience applying data modeling, data quality, and CI/CD practices.

• Technical Knowledge

  • Snowflake architecture and components, including virtual warehouses, databases, schemas, and Snowflake-specific features such as Snowpark, Streams, and Tasks.
  • Advanced SQL programming and ETL/ELT pipeline development in cloud environments.
  • Data modeling, data integration, data quality frameworks, data lineage, and observability.
  • Cloud-based data engineering and AWS services such as S3, Lambda, and Glue.
  • Software engineering principles and development practices, including version control, automated testing, code reviews, and CI/CD.
  • Data pipeline performance optimization, operational automation, and cost management.
  • Familiarity with AI agent development and AI-assisted coding tools, such as GitHub Copilot and Cursor, is an advantage.

• Skills

  • Analytical Thinking and Problem-Solving
  • Technical Troubleshooting and Root Cause Analysis
  • Data Quality and Attention to Detail
  • Requirements Analysis and Solution Development
  • Stakeholder Management and Communication
  • Cross-functional Collaboration and Teamwork
  • Technical Ownership and Accountability
  • Continuous Improvement and Process Optimization
  • Adaptability and Continuous Learning
  • Technical Documentation and Knowledge Sharing