Senior Data Engineer (AWS & Snowflake)

blaseek

Taguig

On-site

PHP 1,800,000 - 3,200,000

Full time

13 days ago

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Job summary

blaseek is seeking a hands-on Senior Data Engineer to design, build, and operate cloud-native data and AI solutions in a production environment. The role emphasizes strong software engineering fundamentals and deep AWS and Snowflake expertise.

You will drive end-to-end data solutions, including data modeling, governance, and performance tuning, while collaborating with stakeholders on analytics and AI initiatives.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, IT, or a related field.
  • At least 7 years of hands-on data/cloud engineering experience.
  • Proven track record delivering cloud-native data solutions in production.
  • Strong AWS and Snowflake expertise.
  • Proficiency in Python and/or Java with clean code and testing practices.
  • Experience with AI/GenAI tools is a plus.

Responsibilities

  • Design, build, and operate production-grade data solutions end-to-end.
  • Design and implement scalable, governed data pipelines using AWS and Snowflake.
  • Model and optimize Snowflake datasets and data structures for performance.
  • Apply software engineering best practices: testing, CI/CD, observability.
  • Collaborate with stakeholders to translate requirements into scalable data solutions.
  • Build cloud-native integrations and automation with AWS services.
  • Use AI-assisted tools to enhance coding, testing, and productivity.
  • Own deployment, release management, and production support.
  • Participate in code reviews and continuous improvement of engineering standards.

Skills

AWS
Snowflake
Python
Java
CI/CD
DevOps
Data modeling
GitHub Copilot

Education

Bachelor's or Master's in CS/Engineering/IT

Tools

Snowflake
AWS
Terraform
GitHub Copilot
CI/CD tooling

Job description

We are looking for a hands-on Senior Data 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.

You Will Have The Following Responsibilities
  • Design, build, and operate production-grade data solutions end-to-end, from architecture and implementation through 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 optimize Snowflake datasets, schemas, and data structures to ensure performance, data quality, consistency, governance, and usability.
  • Apply software engineering best practices including clean code, modular design, automated testing, CI/CD, observability, secure development, and maintainable architecture.
  • Partner with business and technical stakeholders to translate business requirements into scalable data engineering solutions and identify opportunities for analytics and AI initiatives.
  • Build cloud-native integrations and automation using AWS services including compute, storage, networking, security, orchestration, and serverless technologies.
  • Utilize AI-assisted engineering tools to improve coding, testing, documentation, debugging, and overall engineering productivity while maintaining high-quality standards.
  • Own deployment, release management, production support, troubleshooting, root cause analysis, performance tuning, and incident resolution.
  • Participate in peer code reviews, pair programming, and continuous improvement of engineering standards and practices.
You Will Have The Following Qualifications
  • Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, Information Technology, Data Science, Artificial Intelligence, or a related technical discipline.
  • At least 7 years of hands-on experience in Data Engineering, Software Engineering, or Cloud Engineering, with a proven track record of delivering enterprise-grade data solutions.
  • Demonstrated experience building and supporting cloud-native data platforms, data pipelines, and data products in production environments.
  • Strong hands-on experience with AWS, including compute, storage, networking, IAM, security, orchestration, monitoring, and serverless or event-driven services.
  • Strong hands-on experience with Snowflake, including data modeling, SQL performance tuning, data pipeline integration, access control, cost optimization, data sharing, and platform governance.
  • Strong proficiency in Python and/or Java, with solid knowledge of software design principles, APIs, automated testing, dependency management, and application maintainability.
  • Experience with AWS AI services such as Amazon Bedrock, and familiarity with Generative AI, Retrieval-Augmented Generation (RAG), AI agents, and responsible AI practices is an advantage.
  • Experience using AI-assisted engineering tools such as GitHub Copilot, Claude, Cursor, or similar as part of daily development.
  • Strong understanding of Git-based workflows, CI/CD, Infrastructure as Code (IaC), DevOps practices, automated testing, and production support.
  • Ability to translate business requirements into technical solutions and deliver scalable, maintainable data platforms.
  • Strong analytical, problem-solving, communication, and stakeholder management skills.
  • Experience working with sensitive and confidential data while implementing governance, security, and compliance controls.
  • AWS certifications (Solutions Architect, Data Engineer, or Machine Learning Engineer Associate) and SnowPro certifications are preferred.
  • Experience in the financial services industry is an advantage.
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