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Data Solutions Engineer (Snowflake)

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Hybrid

Data Solutions Engineer (Snowflake)

Ascendion

Data Solutions Engineer (Snowflake)

Skills

SQL QueriesData EngineeringPythonData ScienceJavaSnowflakeData AnalysisMachine LearningAIAWS

2 months ago

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Important information


Contract type:

Permanent

Location:

Taguig, Metro Manila, Philippines

Work mode:

Hybrid

Published on:

19 August 2026

What they need


Job Title: Data Solutions Engineer (Snowflake)

Location: BGC, Taguig

Set-up: Hybrid 3x onsite/week

Schedule: Shifting, Monday-Friday

Minimum Required Skills: Data Engineering/Data Modeling, Snowflake, AWS, DevOps, Python/Java

About the role

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.

Key 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.

About you

  • Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence / Machine Learning, or a related technical discipline.
  • 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.
  • Demonstrated ability to build and operate data products, cloud services, or AI-enabled solutions with measurable business outcomes and clear operational ownership.
  • 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.
  • Deep hands-on Snowflake experience is required, including data modelling, SQL performance tuning, pipeline integration, access control, cost/performance optimisation, data sharing, and platform governance.
  • Strong proficiency in Python and/or Java, with solid understanding of software design principles, APIs, automated testing, packaging, dependency management, and production maintainability.
  • Strong hands-on engineering mindset, with a focus on code quality, sound design decisions, maintainability, and effective collaboration in team-based environments.
  • Strong familiarity with the software development lifecycle, Git-based workflows, CI/CD, infrastructure-as-code concepts, automated testing, DevOps practices, and production support.
  • Ability to translate ambiguous business problems into clear technical scopes, iterative delivery plans, and measurable success criteria.
  • Strong collaboration and communication skills, with the ability to work closely with business stakeholders and cross-functional technology teams.

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