Data Engineer II (Alabang)

What will you do

• Design, develop, and maintain scalable data pipelines and ETL processes to support data integration and analytics.
• Collaborate with data architects, modelers and IT team members to help define and evolve the overall cloud-based data architecture strategy, including data warehousing, data lakes, streaming analytics, and data governance frameworks
• Collaborate with data scientists, analysts, and other business stakeholders to understand data requirements and deliver solutions.
• Optimize and manage data storage solutions (e.g., S3, Snowflake, Redshift) ensuring data quality, integrity, security, and accessibility.
• Implement data quality and validation processes to ensure data accuracy and reliability.
• Develop and maintain documentation for data processes, architecture, and workflows.
• Monitor and troubleshoot data pipeline performance and resolve issues promptly.
• Consulting and Analysis: Meet regularly with defined clients and stakeholders to understand and analyze their processes and needs. Determine requirements to present possible solutions or improvements.
• Technology Evaluation: Stay updated with the latest industry trends and technologies to continuously improve data engineering practices.

What do you need to succeed

• Associate degree in Computer Science with a minimum of 4 years experience or Bachelor degree in Computer Science, or related field with a minimum of 2 years of experience or a Master degree in Computer Science, with minimum 1 year of experience or relevant Business or IT experience of minimum of 4 years.
• Moderate level of technical understanding and demonstrated knowledge in integrating data between applications and data warehouses
• Knowledge of project management and experience working on project teams required.
• Moderate knowledge of and experience with life cycle methodology,
• Exposure to or experience in Expertise in one or more of a major cloud platform (AWS, Azure or GCP)
• Moderate knowledge of and experience with the software development lifecycle.
• Experience working in product and devops teams and contributing to a successful outcome

Mandatory skills:

• 4+ years of progressive experience in data engineering, with a significant portion dedicated to cloud-based data platforms.
• ETL/ELT Tools: Hands-on experience with ETL/ELT tools and orchestrators (e.g., Apache Airflow, Azure Data Factory, AWS Glue, dbt).
• Data Governance: Understanding of data governance, data quality, and metadata management principles.
• AWS Experience
• Attendance and schedule adherence are required for this position