Snowflake Data Engineer
Summary
Senior hands-on data engineer who designs, builds, and operates production-grade data pipelines and data products on AWS and Snowflake, covering data modeling, CI/CD, and production operations, with AI-assisted engineering as part of daily work. Hybrid role in BGC, Taguig (3 days onsite/week) on a shifting schedule.
Job Title: Snowflake Data Engineer
Location: BGC, Taguig
Set-up: Hybrid 3x onsite/week
Schedule: Shifting
Minimum Skills Required: Data Engineering/Analytics, Snowflake Platform, AWS Cloud Services , SQL Scripting
We are looking for a hands-on senior solution engineer who can design, build, and operate robust cloud-native data and AI solutions. The ideal candidate combines strong software engineering fundamentals with deep practical experience in AWS and Snowflake.
Responsibilities:
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.
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.
Model, curate, and optimise Snowflake datasets, schemas, and data structures in line with enterprise platform standards, ensuring performance, quality, consistency, and usability for downstream consumers.
Apply strong software engineering practices, including clean code, modular design, automated testing, CI/CD, observability, secure development, and maintainable architecture.
Partner with business and technical stakeholders to translate requirements into robust data solutions, prioritise delivery, and identify opportunities to enable advanced analytics and AI use cases.
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.
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.
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.