Lead Data Engineer

Yondu, Inc.; Mandaluyong; On-site; PHP 2,000,000 - 3,500,000; Full time

Job summary

Yondu, Inc. is seeking a Lead Data Engineer to design, build, and maintain scalable data pipelines across cloud environments, enabling migration from legacy systems to modern data infrastructures.

The role collaborates with product, analytics, and data science teams to deliver reliable data solutions, data marts, and targeted extracts while ensuring governance and operational excellence.

Qualifications

• 8+ years of Data Engineering experience with large-scale data pipelines.
• Experience designing and optimizing scalable data solutions in cloud environments.

Responsibilities

• Design, build, and optimize automated data pipelines and data models for cloud platforms.
• Lead large-scale data migration projects with minimal business disruption.
• Collaborate with product, analytics, and data science teams to meet requirements.
• Develop data marts and custom extractions aligned to reporting needs.
• Monitor pipeline health, troubleshoot incidents, and implement fixes.
• Document workflows, schemas, and runbooks for stability.
• Mentor junior engineers and drive best practices.

Skills

Python

SQL

Databricks

Snowflake

ETL/ELT tooling

Tools

ETL/ELT tooling

Cloud data platforms

Job description

• The Lead Data Engineer is responsible for designing, developing, and maintaining scalable data engineering solutions that support the migration from legacy big data platforms to modern, cloud-based data environments. The role ensures reliable data operations while enabling ongoing and new business initiatives.

Duties and Responsibilities

• Design, build, and optimize automated data pipelines, ETL/ELT processes, and data models to ingest, process, and store large volumes of data within cloud-based platforms.


• Support large-scale data migration initiatives, ensuring data accuracy, performance efficiency, and minimal business disruption.


• Develop and maintain ETL/ELT workflows to ingest, transform, and load data from multiple internal and external sources with a focus on scalability and reliability.


• Partner with business, analytics, and product teams to translate data requirements into effective technical solutions that support strategic initiatives.


• Design and deliver data marts and customized data extractions aligned with business and reporting needs.


• Ensure compliance with enterprise data governance, security, and regulatory standards.


• Monitor data pipeline health and performance, troubleshoot data incidents, and implement preventive and corrective measures.


• Document data workflows, schemas, technical specifications, and operational runbooks to support operational stability and knowledge transfer.


• Collaborate closely with product owners, data architects, and data scientists to maintain a reliable and efficient data infrastructure.


• Drive continuous improvement of data engineering practices, tools, and automation frameworks.


• Provide technical guidance and mentorship to junior engineers through code reviews, best-practice sharing, and troubleshooting support.


• Manage and deliver multiple data engineering initiatives concurrently while meeting quality, scope, and timeline expectations.

Required Experience, Technical Knowledge, and Skills

Experience

• At least 8 years of total Data Engineering experience, with strong exposure to large-scale data pipelines, ETL/ELT development, and enterprise or cloud-based data platforms.


• Proven experience designing, building, and optimizing scalable data solutions in modern data environments.

Knowledge

• Python – At least 4 out of 5 proficiency level, with strong hands-on experience in data transformation, automation, and pipeline development.


• SQL – At least 3 out of 5 proficiency level, with demonstrated capability in complex queries, data modeling, and performance tuning.


• Experience working with modern data cloud platforms, such as Databricks and/or Snowflake.


• Platform and Cloud Exposure - Currently working with or has recent hands-on experience in enterprise-grade cloud data ecosystems. With a strong understanding of cloud-native data architecture and best practices.

Soft Skills

• Strong verbal and written communication skills


• Demonstrated leadership and technical influence


• Strong analytical, critical thinking, and problem-solving abilities


• Process orientation with the ability to enforce standards and best practices


• Strong organizational, multitasking, and time-management skills


• Stakeholder and cross-functional collaboration skills