URGENT - (Senior-Lead) Data Engineer

NCS Philippines; Taguig; Hybrid; PHP 1,200,000 - 2,400,000; Full time

Job summary

NCS Philippines Lead Data Engineer role focused on designing, developing, and maintaining scalable data pipelines and ETL/ELT processes to support migration from legacy big data platforms to modern cloud environments.

The position requires collaboration with product, analytics, and data science teams to deliver reliable, scalable data solutions, govern data assets, and mentor junior engineers for ongoing improvements.

Qualifications

• At least 8 years of total data engineering experience.
• Experience with large-scale data pipelines in cloud environments.
• Strong abilities in data modeling, ETL/ELT, and governance.

Responsibilities

• Design, build, and optimize automated data pipelines and data models.
• Support large-scale data migration initiatives to cloud platforms.
• Develop ETL/ELT workflows from multiple data sources with scalability.
• Collaborate with analytics, product, and business teams on data solutions.
• Deliver data marts and extracts aligned with reporting needs.
• Ensure compliance with data governance, security, and regulatory standards.
• Monitor pipeline health, troubleshoot incidents, and implement fixes.
• Document workflows, schemas, and runbooks for stability.
• Mentor junior engineers and drive improvement in data engineering practices.
• Manage multiple initiatives concurrently while meeting quality and timelines.

Skills

Python

SQL

Databricks/Snowflake

Azure Data Services

Tools

Databricks

Snowflake

Azure Data Factory

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.

  • Experience with cloud services, preferably Microsoft Azure (e.g., Azure Data Factory, Azure Synapse, Azure Storage, etc.).

  • 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