We are looking for a highly skilled Senior Data Engineer to design, develop, maintain, and optimize scalable data solutions on Google Cloud Platform (GCP). The successful candidate will be responsible for building reliable batch and real-time data pipelines, implementing ETL/ELT processes, managing data ingestion and transformation, ensuring data quality, and supporting the reliability and scalability of the overall data ecosystem.

The ideal candidate will have strong hands-on experience with GCP Dataflow, Cloud Composer, BigQuery, SQL, Python or Java, Apache Beam, Airflow, Pub/Sub, data modeling, ETL/ELT, monitoring, logging, and cloud-based data engineering.

Key Responsibilities

Data Engineering & Pipeline Development

• Design, develop, and maintain scalable and reliable data pipelines.

• Build batch and streaming pipelines for data collection, processing, transformation, and integration.

• Implement ETL/ELT processes across different systems and environments.

• Optimize pipelines for performance, scalability, reliability, and maintainability.

• Support data migration, deployment, and production activities.

Google Cloud Platform

• Develop and manage data engineering solutions using Google Cloud Platform.

• Work with BigQuery, Dataflow, Cloud Composer, Pub/Sub, and Cloud Spanner where applicable.

• Design cloud-based data processing solutions capable of handling high-volume workloads.

• Optimize cloud resources and workflows for performance and reliability.

Batch & Real-Time Data Processing

• Develop and maintain batch and real-time/streaming data pipelines.

• Build event-driven data workflows using Pub/Sub and Dataflow.

• Process high-throughput data while maintaining accuracy and reliability.

• Troubleshoot pipeline failures, processing delays, and data inconsistencies.

SQL, Python/Java & Data Frameworks

• Develop complex and optimized SQL queries for extraction, transformation, aggregation, validation, and analysis.

• Develop reusable and production-ready components using Python or Java.

• Use Apache Beam for scalable data processing.

• Use Apache Airflow / Cloud Composer for workflow orchestration.

• Troubleshoot and optimize pipeline and application-level issues.

Data Ingestion & File Processing

• Design and implement data ingestion pipelines for multiple source systems.

• Handle structured and semi-structured data formats such as Avro, Parquet, JSON, and CSV.

• Validate incoming data for completeness, consistency, accuracy, and integrity.

• Troubleshoot file ingestion and data processing failures.

Data Quality & Reliability

• Implement data validation and reconciliation mechanisms.

• Identify and resolve data quality issues across source, processing, and target systems.

• Ensure pipelines are reliable and capable of supporting production workloads.

• Monitor data processing activities and proactively address failures and anomalies.

Monitoring & Troubleshooting

• Monitor data pipelines using Google Cloud Monitoring and Cloud Logging.

• Develop and maintain monitoring, alerting, and operational mechanisms.

• Investigate system errors, pipeline failures, performance issues, and data anomalies.

• Perform root-cause analysis and implement corrective actions.

Data Modeling & Architecture

• Apply strong data engineering and data modeling principles.

• Design scalable data structures and processing architectures.

• Support analytical and transactional data solutions.

• Ensure data solutions meet performance, security, scalability, and maintainability requirements.

Required Qualifications & Experience

• Minimum 2 years of relevant experience in Data Engineering or related roles.

• Hands-on experience with Google Cloud Platform (GCP).

• Strong experience with BigQuery, Dataflow, and Cloud Composer.

• Experience with batch and real-time/streaming data processing.

• Strong command of SQL.

• Proficiency in Python or Java.

• Experience with Apache Beam and/or Apache Airflow.

• Strong understanding of ETL/ELT and data modeling.

• Experience working with Avro, Parquet, JSON, and CSV.

• Strong debugging, troubleshooting, and problem-solving capabilities.

• Experience with cloud monitoring, logging, and alerting.

Preferred Skills

• Cloud Spanner

• Google Cloud Certified Professional Data Engineer

• CI/CD for data infrastructure

• Terraform / Infrastructure as Code

• GitHub Actions

• Data Governance

• GCP Security

• IAM, KMS, and DLP

• Cloud Infrastructure Automation

Education & Certification

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related technical field is preferred.

• Equivalent technical qualifications and relevant professional experience may be considered.

• Google Cloud Certified Professional Data Engineer certification is preferred.

Soft Skills

• Strong analytical and problem-solving skills.

• Excellent troubleshooting and debugging abilities.

• Strong attention to detail.

• Good communication and stakeholder management skills.

• Ability to work independently and collaboratively.

• Ability to manage multiple technical priorities.

• Strong ownership, accountability, and proactive problem-solving approach.

• Ability to work effectively in a fast-paced technology environment.

• Willingness to work in a shifting schedule.

Work Location & Eligibility

• Work Mode: Onsite

• Location: Manila / Taguig, Philippines

• Candidates must currently be located in the Philippines.

• Candidates must have the legal right to live and work in the Philippines.

• Candidates must be willing to work from the office and follow a shifting schedule.

• Candidates without the required work authorization are not eligible.

• Candidates should not have an active or recent application with the hiring organization.

• Candidates should not be currently or recently employed by the hiring organization.

Recruitment Process

The recruitment process may include initial CV screening, CV validation, technical assessment, evaluation of relevant experience and qualifications, and client review/selection.

Pre-Screening Questions

1. How many years of relevant Data Engineering experience do you have?

2. How many years of hands-on experience do you have with GCP?

3. Please share your relevant technical and soft skills.

4. What was your last drawn salary?

5. What is your expected salary?

6. Are you comfortable working onsite in Manila/Taguig with a shifting schedule?

7. Are you currently located in the Philippines and legally authorized to work there?

8. Do you currently have an active application or Workday account with the hiring organization?

9. Have you been currently or recently employed by the hiring organization?