Data Engineer

4 days ago

Santa Maria, Philippines Motolite Full time ₱104,000 - ₱130,878 per year

Job Summary

The Data Engineer is responsible for designing, building, and maintaining the data infrastructure that supports analytics, reporting, and business decision-making. This role involves developing and optimizing data pipelines, ensuring data quality and accessibility, and integrating data from multiple sources into scalable data systems. The Data Engineer works closely with data analysts, data scientists, and other stakeholders to provide reliable, efficient, and secure data solutions that enable the organization to leverage data as a strategic asset.

DAILY DUTIES AND RESPONSIBILITIES

 Design, develop, and maintain data pipelines to integrate data from equipment, testers, IoT devices, and external systems into enterprise and cloud platforms.

 Implement ETL/ELT workflows and transformations to prepare raw operational data for analytics, dashboards, and AI/ML workloads.

 Build and optimize relational, dimensional, and time-series data models for manufacturing and business intelligence use cases.

 Write and maintain SQL and Python scripts; automate workflows with orchestration tools and manage code with version control.

 Monitor and troubleshoot pipeline performance, resolving latency, reliability, and data quality issues.

 Apply data governance practices, including lineage, validation, and access controls, to ensure secure and trusted data delivery.

 Collaborate with BI, IT, and data science teams to support analytics requirements and continuous process improvements.

JOB SPECIFICATIONS

Minimum Education: Bachelor's degree in Computer Science, Data Science, Engineering (e.g., Chemical, Industrial, Electrical), Applied Physics, Mathematics, or other closely related analytical or technical fields; Latin honors preferred.

Work Experience: 2-3 years of professional experience in data engineering, data integration, or pipeline development, including hands-on work with SQL, ETL/ELT workflows, and cloud or enterprise data platforms; exposure to manufacturing, IoT, or PLC data sources is an advantage.

Special Training/Skills Required: Proficiency in SQL and relational database systems for querying, tuning, and optimization; strong Python skills for data processing and automation; experience designing and managing ETL/ELT pipelines for both batch and streaming workflows; expertise in data modeling to support analytics and ML workloads; familiarity with big data frameworks and message queue systems; hands-on experience with cloud data platforms for scalable storage and compute; knowledge of workflow orchestration and version control tools for automation and reproducibility; solid understanding of data governance, lineage, and security practices; strong analytical and troubleshooting skills to ensure pipeline reliability, performance, and data integrity.

Other Preferred Skills/Competencies: Exposure to ML/AI workflows and agent-based automation for anomaly detection and intelligent monitoring; effective communication and collaboration skills to work with BI, IT, and operations teams; ability to prepare clear technical documentation and data dictionaries; strong problem-solving and critical-thinking skills for diagnosing data quality or performance issues; adaptability to emerging tools, frameworks, and cloud technologies.

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