Data Engineer (Cloud & Modern Data Stack Focus)

Katrina Mojica- Freelance Recruiter; General Santos; On-site; PHP 446,400 - 669,600; Full time

Job summary

A leading freelance recruitment service is seeking a technically skilled Data Engineer to enhance cloud-based analytics capabilities. The ideal candidate will design and optimize data pipelines using tools like Google Cloud Platform, dbt, and Airbyte. Responsibilities include collaborating with teams to ensure scalable data models and maintaining data quality. Candidates should have a bachelor’s degree and 3+ years in data engineering, emphasizing strong SQL and cloud experience.

Qualifications

• 3+ years in data engineering, ELT development, or cloud analytics engineering.
• Strong working knowledge of SQL and modern data platform environments.
• Experience in retail, finance, supply chain, or e-commerce is advantageous.

Responsibilities

• Design, develop, and maintain data pipelines in cloud-based analytics environments.
• Build and manage reliable ELT pipelines that centralize data.
• Collaborate with Analytics Engineers to ensure scalable data models.

Skills

SQL skills

ELT development

Experience with cloud data warehouses

Data structure understanding

Familiarity with Google Cloud Platform and BigQuery

Analytical and problem-solving skills

Communication skills

Education

Bachelor’s degree in Computer Science, IT, Engineering, or related field

Tools

Google Cloud Platform

BigQuery

dbt

Airbyte

Dataform

Job description

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, and validation.
• 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

• Bachelor’s 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 with dbt, 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.