Senior Solution Engineer - Java and Snowflake

SPI GLOBAL CONTENT HOLDING PTE. LTD.; Singapore; On-site; SGD 200,000 - 260,000; Full time

Job summary

SPI GLOBAL CONTENT HOLDING PTE. LTD. seeks an experienced Senior Software/Data Engineer to design and operate end-to-end data and software solutions. The role focuses on building scalable data pipelines on AWS and Snowflake, with strong emphasis on governance, performance, and security.

The candidate will drive implementation of data products, collaborate with business and technical stakeholders, and uphold robust engineering practices including testing, deployment, and observability.

Qualifications

• Bachelor's or Master's degree in CS/SE/Data Science/AI/ML or related field.
• 7+ years in hands-on software, solutions, or data engineering with production-grade delivery.
• Experience building and operating data products, cloud services, or AI-enabled solutions with measurable outcomes.
• Strong AWS experience across core services, security, orchestration, and monitoring; AWS certs preferred.
• Deep Snowflake experience: data modelling, SQL tuning, pipelines, governance; Snowflake certs a plus.

Responsibilities

• Design, build, and operate production-grade software and data solutions end-to-end.
• Develop reliable, scalable data pipelines and products using AWS and Snowflake.
• Model and optimize Snowflake datasets for enterprise use with high performance and quality.
• Apply software engineering best practices: clean code, testing, CI/CD, observability.
• Collaborate with stakeholders to translate requirements into robust data solutions.

Skills

AWS

Snowflake

Data engineering

Software engineering

CI/CD

Observability

AI/ML integration

Education

Bachelor's or Master's in CS/SE/Data Science/AI/ML

Tools

Snowflake

SQL

Python

AWS

Job description

Key Responsibilities

1. Design, build, and operate production-grade software and data solutions end-to-end, from problem definition and architecture through implementation, deployment, monitoring, and continuous improvement.

2. Design and implement reliable, scalable, secure, and well-governed data pipelines and data products using AWS and Snowflake across structured, semi-structured, and unstructured data sources.

3. Model, curate, and optimize Snowflake datasets, schemas, and data structures in line with enterprise platform standards, ensuring performance, quality, consistency, and usability for downstream consumers.

4. Apply strong software engineering practices, including clean code, modular design, automated testing, CI/CD, observability, secure development, and maintainable architecture.

5. Partner with business and technical stakeholders to translate requirements into robust data solutions, prioritize delivery, and identify opportunities to enable advanced analytics and AI use cases.

6. Use AI-assisted engineering as a standard part of daily development work to accelerate coding, refactoring, documentation, testing, debugging, and solution exploration while maintaining strong engineering judgement and quality standards.

7. Build cloud-native integrations and automation on AWS, making effective use of services such as compute, storage, networking, security, orchestration, event-driven architectures, and managed AI services where appropriate.

8. Own deployment, release, and production operations, including troubleshooting, root-cause analysis, performance tuning, incident resolution, peer code reviews, pair programming, and reuse of proven engineering patterns.

Skills and Experience Required

1. Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence / Machine Learning, or a related technical discipline.

2. 7+ years of professional experience in a hands-on software engineering, solution engineering, or data engineering role, with a proven track record of delivering production-grade systems in enterprise environments.

3. Demonstrated ability to build and operate data products, cloud services, or AI-enabled solutions with measurable business outcomes and clear operational ownership.

4. Deep hands-on AWS experience is required, including practical knowledge of core services for compute, storage, networking, identity and access management, security, orchestration, monitoring, and serverless or event-driven architectures. AWS certification is preferred, ideally AWS Certified Solutions Architect – Associate, AWS Certified Data Engineer – Associate, or AWS Certified Machine Learning Engineer – Associate.

5. Deep hands-on Snowflake experience is required, including data modelling, SQL performance tuning, pipeline integration, access control, cost/performance optimization, data sharing, and platform governance. SnowPro® Core Certification or advanced Snowflake certifications are a plus.