Data Engineer

Asia Select, Inc. (ASI); Makati; On-site; PHP 1,000,000 - 2,000,000; Full time

Job summary

Asia Select, Inc. (ASI) is seeking an experienced Data Engineer to design, develop, and operate large-scale ETL/ELT pipelines across enterprise apps, APIs, and cloud platforms in Metro Manila.

The role emphasizes Snowflake data models, data marts, and analytics datasets for enterprise reporting. You will build AI-enabled data workflows with Cortex and Bedrock, mentor junior engineers, and collaborate with global teams to ensure data reliability and governance.

Qualifications

• Bachelor's degree or equivalent professional experience.
• 4+ years of experience in Data Engineering, Software Engineering, Analytics Engineering, Data Integration, or related discipline.
• Advanced SQL skills including complex transformations, performance optimization, and data modeling.
• Strong Python programming skills and production-grade experience.
• Hands-on experience designing, developing, and supporting ETL/ELT pipelines in cloud/enterprise environments.
• Experience with Snowflake, AWS, Azure, Databricks, or similar platforms.
• Experience integrating enterprise applications using APIs, cloud services, and event-driven architectures.
• Excellent written and verbal English communication and ability to discuss with global stakeholders.
• Ability to manage projects independently and support production environments.

Responsibilities

• Design, develop, test, deploy, and maintain ETL/ELT pipelines across enterprise applications, APIs, databases, cloud platforms, file systems, and events.
• Build and support data integrations using REST/GraphQL APIs, cloud storage, secure file transfers, database connectors, and message-based architectures.
• Develop, optimize, and maintain Snowflake databases, data models, data marts, and analytical datasets for reporting.
• Create scalable data solutions using SQL, Python, Snowpark, and automation tools for operations and analytics.
• Build AI-enabled data pipelines using Cortex, Bedrock, embeddings, vector search, and RAG.
• Monitor pipelines, troubleshoot issues, perform root-cause analysis, and implement long-term fixes for reliability.
• Develop technical docs, architecture diagrams, runbooks, and support procedures for deployed solutions.
• Collaborate with cross-functional teams to automate processes, improve data quality, and enhance enterprise reporting.
• Support data governance, metadata management, and security controls, following data management best practices.
• Contribute to standards, reusable frameworks, and continuous improvement initiatives.

Skills

Advanced SQL

Python

ETL/ELT pipelines

Snowflake

APIs integration

Cloud platforms

Data modeling

Documentation

English communication

Problem solving

Education

Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Engineering, Mathematics, or related field

Tools

Snowflake

Snowpark

AWS

Azure

Databricks

REST/GraphQL

Job description

• Design, develop, test, deploy, and maintain ETL/ELT pipelines across enterprise applications, APIs, databases, cloud platforms, file systems, and event-driven services.
• Build and support data integrations using REST and GraphQL APIs, cloud storage, secure file transfers, database connectors, and message-based architectures.
• Develop, optimize, and maintain Snowflake databases, data models, data marts, analytical datasets, and enterprise reporting solutions.
• Create scalable data solutions using SQL, Python, Snowpark, cloud services, and automation tools to support business operations and analytics initiatives.
• Build AI-enabled data pipelines and workflows utilizing technologies such as Snowflake Cortex, Amazon Bedrock, embeddings, vector search, document processing, and retrieval-augmented generation (RAG).
• Monitor data pipelines, troubleshoot production issues, conduct root cause analysis, and implement long-term corrective solutions to ensure reliability and performance.
• Develop technical documentation, architecture diagrams, operational runbooks, and support procedures for deployed solutions.
• Collaborate with cross-functional teams to identify automation opportunities, improve data quality, streamline business processes, and enhance enterprise reporting capabilities.
• Support enterprise data governance initiatives, metadata management, security controls, and best practices for data management.
• Contribute to technical standards, reusable frameworks, engineering best practices, and continuous improvement initiatives.

QUALIFICATIONS & REQUIREMENTS:

• You must hold a Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Engineering, Mathematics, or a related field, or possess equivalent professional experience.
• You must have at least 4 years of experience in Data Engineering, Software Engineering, Analytics Engineering, Data Integration, or a related discipline.
• You must have advanced SQL skills, including complex data transformations, performance optimization, procedural logic, and data modeling.
• You must possess strong Python programming skills and experience developing production-grade applications, services, or data-processing solutions.
• You must have hands-on experience designing, developing, and supporting ETL/ELT pipelines within cloud or enterprise environments.
• You must have experience working with modern cloud data platforms such as Snowflake, AWS, Azure, Databricks, or similar technologies.
• You must have experience integrating enterprise applications using APIs, databases, cloud services, and event-driven architectures.
• You must demonstrate strong analytical thinking, troubleshooting, technical documentation, and problem-solving skills.
• You must be capable of independently managing projects, making sound technical decisions, and supporting production environments with minimal supervision.
• You must possess excellent written and verbal English communication skills and be comfortable participating in technical discussions with global stakeholders.

PREFERRED QUALIFICATIONS:

• Advanced experience with Snowflake, including Snowpark, Streams, Tasks, Dynamic Tables, Stored Procedures, and performance optimization.
• Experience with AWS serverless technologies, orchestration services, monitoring tools, and cloud security best practices.
• Exposure to Generative AI, Snowflake Cortex, Amazon Bedrock, document intelligence, embeddings, vector databases, and RAG implementations.
• Experience integrating enterprise platforms such as Oracle Fusion, ServiceNow, Salesforce, Microsoft Graph, or monitoring solutions.
• Knowledge of BI and analytics platforms such as Amazon QuickSight, Power BI, Tableau, or similar tools.
• Experience working within managed services, consulting, technology services, or multi-customer enterprise environments.