Data Engineer (Cloud & Modern Data Stack Focus), General Santos

Job Summary

We are looking for a technically skilled and forward-thinking Data Engineer to strengthen our cloud-based analytics and data platform capabilities. This role will focus on designing, building, and optimizing scalable pipelines and transformation workflows within a modern data stack, with Google Cloud Platform, dbt, and Airbyte experience considered strong

advantages.

This position is critical in helping build and scale a modern cloud-native data environment, ensuring that data is ingested, transformed, validated, and delivered accurately and efficiently. You will work closely with business stakeholders, Analytics Engineers, IT, and DevOps teams to improve the reliability, usability, and scalability of core analytical and operational data.

Key Responsibilities

• Design, develop, and maintain data pipelines and transformation workflows within cloud-based analytics environments.
• Build and manage reliable ELT pipelines that move data from operational systems, APIs, files, and third-party platforms into centralized cloud reporting and analytics environments.
• Work closely with teams supporting Google Cloud Platform and modern data stack tools to understand source structures, business logic, and reporting dependencies.
• Develop and optimize SQL queries and transformation logic for data processing reconciliation, modeling, andvalidation.
• Support the integration of source systems into the broader enterprise cloud data architecture.
• Collaborate with Analytics Engineers to ensure scalable, reusable, and future-proof data models.
• Investigate data discrepancies, reconcile mismatches, and troubleshoot issues related to ingestion, transformation, and reporting outputs.
• Maintain clear technical documentation covering pipeline logic, source mappings, dependencies, and operational procedures.
• Contribute to data quality and governance efforts by helping define control points, validation checks, testing standards, and reconciliation logic.
• Design, manage, and provision IAM roles and access policies across cloud data platforms to ensure secure, controlled, and compliant access to datasets, pipelines, and supporting services.

Skills / Competencies

• Strong SQL skills, including joins, aggregations, transformations, performance tuning, and troubleshooting.
• Hands-on experience with ELT development across cloud-based analytics environments.
• Experience working with cloud data warehouses, ingestion tools, and transformation frameworks.
• Good understanding of data structures, modular transformation logic, and pipeline design.
• Familiarity with Google Cloud Platform / BigQuery / dbt / Airbyte / Dataform is a strong advantage.
• Ability to understand how raw source data should be transformed and modeled for reporting and analytics.
• Strong analytical and problem-solving skills with high attention to detail.
• Good communication skills and the ability to work across technical and business teams.
• Comfortable working in environments where automation, standardization, and scalability are as important as coding.

Qualifications:

• Bachelors degree in Computer Science, Information Technology, Engineering, Data Analytics, or a related field.
• 3+ years in data engineering, ELT development, cloud analytics engineering, or modern data platform environments.
• Strong working knowledge of SQL and cloud-based data warehouses.
• Experience with Google Cloud Platform, BigQuery, or similar cloud data platforms.\
• Experience witDBT,t, Airbyte, Dataform, or related modern data stack tools is a strong plus.
• Experience in retail, finance, supply chain, e-commerce, or other operationally intensive industries is advantageous.