IT Data Engineer (Snowflake)

Infor

Manila

On-site

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

Full time

6 days ago
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Job summary

Infor in Manila seeks an experienced IT Data Engineer to lead Snowflake migration and modernization efforts, building scalable data solutions for analytics, automation, and AI initiatives. You will design ELT/ETL pipelines, implement semantic models, and partner with data scientists, analysts, and engineers to deliver reliable, governed data assets that accelerate decision-making and innovation.

This role requires hands-on Snowflake development, strong SQL/Python skills, and a proactive

Qualifications

  • Extensive Snowflake development experience, including ingestion, ELT/ETL, and data modeling.
  • Proficient in SQL and Python for data transformation and automation.
  • Knowledge of Data Vault concepts (hubs, links, satellites) and modern warehouse patterns.
  • Experience building production-grade data pipelines with reliability and observability.
  • Familiarity with CI/CD, code reviews, and scalable engineering practices.
  • Strong stakeholder engagement and ability to translate technical concepts.

Responsibilities

  • Design, build, and optimize Snowflake-based data solutions for analytics and AI readiness.
  • Develop robust ELT/ETL pipelines and data workflows.
  • Create semantic models and support Cortex/AI-driven initiatives.
  • Collaborate with business and technical teams to gather requirements.
  • Mentor junior engineers and promote engineering standards.
  • Ensure data quality, security, and governance across platforms.

Skills

Snowflake core
ELT/ETL pipelines
SQL
Python
Data Vault
Data modeling
Security & governance
CI/CD
Data warehousing

Tools

dbt
Airflow
Snowflake
Git
Cortex

Job description

Description

The IT Data Engineer will play a key role in Infor’s Snowflake migration and modernization initiative, designing and developing scalable Snowflake-based data solutions that support analytics, automation, and AI-driven capabilities. The role is primarily focused on hands-on Snowflake development, including data ingestion, data pipeline development, semantic layer creation, and Snowflake Cortex-enabled AI initiatives.

Department: Information Technology

Location: Manila

A Typical Day In The Life Includes
Data Platform & Engineering
  • Design, build, and optimize scalable, secure, and high-performing data solutions in Snowflake including ingestion, transformation, modeling, and consumption layers.
  • Develop and maintain robust ELT/ETL pipelines, data workflows, and transformation frameworks to support reporting, analytics, operational use cases, and AI initiatives.
  • Build and optimize Snowflake data models using best practices for performance, maintainability, scalability, and cost efficiency.
  • Ensure strong data quality, reliability, observability, security, and governance through testing, monitoring, documentation, and operational best practices.
  • Drive continuous improvement in data engineering practices including CI/CD, code reviews, reusable frameworks, automation, and production support readiness.
Semantic Layer & AI Readiness
  • Lead the implementation of semantic layer foundations using tools such as Snowflake Cortex Analyst YAML, dbt Metrics, or similar semantic modeling frameworks that make business data easier to discover, understand, and consume.
  • Help prepare the data platform for AI readiness, including enabling structured, governed, and well-documented data assets that support AI/ML, copilots, intelligent agents, and natural language data experiences.
  • Support data contracts and data product design practices that ensure upstream/downstream data reliability and enable scalable AI-ready data sharing across teams.
  • Leverage Snowflake-native capabilities including Horizon Catalog, Cortex-powered workflows, streams, tasks, and dynamic tables for metadata visibility, cataloging, lineage, and observability.
  • Contribute to enablement of modern tooling such as dbt, MCP-style integration patterns, Kiro, and Copilot/AI-assisted engineering practices.
Stakeholder Engagement & Delivery
  • Act as an embedded engineering partner—engaging directly with projects end to end, from requirements clarification, data assessment, and design through build, deployment, testing, and post-production support.
  • Partner closely with business stakeholders, analysts, data scientists, architects, and cross-functional engineering teams to shape and deliver solutions.
  • Translate technical concepts clearly for both technical and non-technical audiences; confidently present designs, recommendations, trade-offs, and progress updates to senior leadership.
  • Mentor associate engineers, promote engineering standards, and contribute to a culture of continuous learning, collaboration, and delivery excellence.
Basic Qualifications
  • Experience in data engineering, analytics engineering, or a related technical role, with strong exposure to modern cloud data platforms.
  • Solid hands-on expertise in Snowflake as a core data platform, including experience with data ingestion and loading patterns, ELT design and implementation, performance tuning and query optimization, virtual warehouse sizing and workload management, cost optimization, secure data sharing and access control, as well as Snowflake-native capabilities such as Streams, Tasks, Dynamic Tables, and other platform features.
  • Solid proficiency in SQL and Python for data transformation, automation, and engineering workflows.
  • Knowledge of Data Vault methodology, including hubs, links, and satellites, and its application within modern data warehousing environments.
  • Solid experience designing and implementing scalable data models, including dimensional modeling, Data Vault modeling, business-friendly consumption models, and semantic-ready structures.
  • Experience building and maintaining production-grade data pipelines with a strong focus on reliability, observability, performance, and maintainability.
  • Strong understanding of modern data warehousing architecture, metadata-driven development, and best practices for building analytics-ready data solutions.
  • Experience supporting AI-readiness initiatives, including preparing trusted, governed, and well-structured data for downstream AI, analytics, and automation use cases.
  • Strong stakeholder engagement skills, with the ability to gather requirements, shape solutions, and collaborate effectively across technical and business teams.
  • Excellent communication, facilitation, and presentation skills, with the ability to explain complex technical concepts clearly and influence decision-making.
  • Strong ownership mindset with the ability to independently drive workstreams and deliver outcomes across the full project lifecycle.
  • Contribution-motivated team player who actively looks for opportunities to improve platforms, optimize processes, and create business value.
Preferred Qualifications
  • Hands-on experience with dbt (data build tool) for transformation, testing, documentation, and modular analytics engineering practices.
  • Experience with orchestration tools such as Airflow or similar workflow schedulers.
  • Familiarity with Snowflake AI and governance capabilities, such as Snowflake Cortex / Cortex-powered development or code assistance, Snowflake Horizon Catalog, Semantic layer or metadata-driven data enablement, and Governance and discoverability capabilities for AI-ready data
  • Exposure to MCP-style integration patterns, modern data product design, or emerging AI/agent-enablement frameworks.
  • Experience with data contracts and data product design to support reliable, governed data sharing across teams and AI consumers.
  • Experience using Copilot, Kiro, or similar AI-assisted engineering tools to improve productivity, code quality, documentation, and delivery speed.
  • Experience with CI/CD pipelines, Git-based development workflows, and release management for data engineering assets.
  • Strong knowledge of data governance, lineage, cataloging, security, and compliance best practices in enterprise environments.
  • Experience working directly with business programs or product teams in a forward-deployed engineering or embedded delivery model.
  • Experience contributing to architecture discussions, technical roadmaps, and platform modernization initiatives.
About Infor

Infor is where ambition meets impact. Join a global community of bold thinkers and innovators, where your expertise doesn't just solve problems. it shapes industries, unlocks opportunities, and creates real-world impact for billions of people. At Infor, you're not just building a career. you're helping to build what's next.

Infor is a global leader in business cloud software products for companies in industry specific markets. Infor builds complete industry suites in the cloud and efficiently deploys technology that puts the user experience first, leverages data science, and integrates easily into existing systems. Over 60,000 organizations worldwide rely on Infor to help overcome market disruptions and achieve business-wide digital transformation.

For more information visit www.infor.com

Our Values

At Infor, we strive for an environment that is founded on a business philosophy called Principle Based Management™ (PBM™) and eight Guiding Principles: integrity, stewardship & compliance, transformation, principled entrepreneurship, knowledge, humility, respect, self-actualization.

We have a relentless commitment to a culture based on PBM™. Informed by the principles that allow a free and open society to flourish, PBM™ prepares individuals to innovate, improve, and transform while fostering a healthy, growing organization that creates long-term value for its clients and supporters and fulfillment for its employees.

Infor is an Equal Opportunity Employer. We are committed to creating a diverse and inclusive work environment. Infor does not discriminate against candidates or employees because of their sex, race, gender identity, disability, age, sexual orientation, religion, national origin, veteran status, or any other protected status under the law. If you require accommodation or assistance at any time during the application or selection processes, please submit a request by following the directions located in the FAQ section.

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