Data Engineer – Data Architecture

Work Location: Manila, Philippines
Work Setup: Onsite
Work Shift: Shifting Schedule
Salary Budget: Confidential (To be discussed during the job offer)
Required Experience: 10+ years preferred; minimum 5 years of relevant experience
Job Function: Data Engineering / Data Architecture
Industry: IT Services / Data & Analytics

Job Summary

We are seeking an experienced Data Engineer – Data Architecture to lead the design, development, and implementation of modern, scalable, cloud-native data platforms. The role involves building and maintaining data pipelines, developing ETL/ELT processes, ensuring data quality, and enabling real-time data processing to support advanced analytics, AI/ML, and digital transformation initiatives.

The ideal candidate will have strong expertise in modern data architecture, cloud platforms, data warehousing, lakehouse technologies, and enterprise data governance.

Key Responsibilities

• Lead end-to-end data architecture and engineering initiatives for large-scale modernization and digital transformation projects.

• Design, develop, and maintain scalable data platforms using cloud services such as Microsoft Azure, AWS, or Google Cloud Platform (GCP).

• Build and optimize data pipelines, ETL/ELT workflows, and data integration processes across multiple systems.

• Implement modern data architecture patterns, including data mesh, data fabric, data virtualization, and knowledge graphs.

• Develop and manage modern data platforms using technologies such as Apache Spark, Databricks, Snowflake, Azure Synapse, BigQuery, Kafka, dbt, and Delta Lake.

• Design logical and physical data models for structured, semi-structured, and unstructured data.

• Develop batch and real-time data processing solutions to support business intelligence, analytics, and AI/ML use cases.

• Establish data governance, metadata management, master data management, data quality, security, and access control standards.

• Collaborate with data engineers, product owners, architects, and business stakeholders to translate business requirements into scalable technical solutions.

• Evaluate and recommend data platforms, tools, and frameworks aligned with enterprise data strategy.

• Implement data cataloging, discovery, and lineage capabilities using tools such as Collibra, Alation, and Microsoft Purview.

• Apply DevOps, DataOps, and CI/CD practices to improve data pipeline deployment, monitoring, reliability, and performance.

• Integrate data platforms with AI/ML solutions and support continuous improvement of data architecture.

Required Skills and Qualifications

• 10+ years of experience in data architecture and data engineering roles preferred, with a minimum of 5 years of relevant experience required.

• Hands-on experience with at least one major cloud platform: Azure, AWS, or GCP. Experience with emerging platforms such as IOMETE is an advantage.

• Strong knowledge of modern data warehousing and lakehouse platforms, including Snowflake, Databricks, Azure Synapse, Amazon Redshift, or Google BigQuery.

• Expertise in ETL/ELT, data integration, and orchestration tools such as dbt, Azure Data Factory, AWS Glue, or Apache Airflow.

• Experience with real-time data streaming technologies such as Apache Kafka and Spark Structured Streaming.

• Strong understanding of data modeling, data quality frameworks, metadata management, and data governance.

• Familiarity with data mesh, data fabric, and data product concepts.

• Experience with data cataloging and discovery tools such as Collibra, Alation, or Microsoft Purview.

• Knowledge of DevOps, DataOps, CI/CD, and automated data pipeline deployment.

• Experience integrating data platforms with AI/ML technologies.

• Strong analytical, problem-solving, communication, and stakeholder-management skills.

• Ability to collaborate effectively with technical teams and business stakeholders.

Work Requirements

• Must be willing to work onsite in Manila, Philippines.

• Must be amenable to a shifting work schedule.

• Must be comfortable working in a collaborative, fast-paced environment.

Recruitment and Screening Process

1. Initial CV review by the CV Reviewer.

2. Candidate endorsement for validation and further CV screening through Workday.

3. Review of the required HRI toolkit, FCV, CV, and screening notes.

4. Final review and endorsement to the client.

Pre-Screening Questions

1. How many years of relevant hands-on experience do you have in data architecture and data engineering?

2. What is your current or last-drawn salary?

3. What is your expected salary?

4. Are you willing to work onsite in Manila on a shifting schedule?

Candidate Submission Guidelines

• Submit the candidate’s latest CV in PDF format.

• Include screening notes aligned with the job requirements.

• Ensure all required validation documents and screening materials are complete.

• Do not disclose the client’s name in the job posting or candidate-facing communications.

Note: The salary budget is confidential and will be discussed during the job offer.