Location: Eton Centris, Quezon City
Work Set Up: Hybrid (twice WFH + thrice RTO)
Salary: Up to Php 115k
The ideal candidate combines strong software engineering fundamentals with hands-on experience in cloud data technologies, ETL development, and modern DevOps practices.
Key Responsibilities
As a Data Engineer, you will:
- Build, enhance, and maintain robust ETL/ELT pipelines using Azure technologies such as Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Microsoft Fabric.
- Design scalable data workflows that support structured and unstructured data across multiple environments.
- Manage and optimize cloud-based storage solutions including Azure Data Lake Storage Gen2 and Azure Blob Storage.
- Partner with data architects, analysts, data scientists, and business stakeholders to deliver reliable and efficient data solutions.
- Improve performance, scalability, and resiliency of enterprise data pipelines and processing frameworks.
- Implement data validation, monitoring, and quality assurance processes to ensure data accuracy and integrity.
- Troubleshoot pipeline failures and production issues while ensuring minimal downtime and fast resolution.
- Maintain technical documentation, deployment procedures, and operational best practices.
- Support CI/CD implementation and automation for data platform deployments and ongoing maintenance.
- Stay informed on emerging technologies and recommend improvements to the organization's data ecosystem.
Required Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline (or equivalent practical experience).
- Professional experience in Data Engineering, ETL development, or related data platform roles.
- Strong hands-on experience with Microsoft Azure data services, including:
- Azure Data Factory
- Azure Synapse Analytics
- Azure Databricks
- Azure Blob Storage
- Azure Data Lake Storage Gen2
- Solid SQL development skills with experience querying relational databases such as SQL Server or PostgreSQL.
- Understanding of software engineering best practices including version control, testing, and CI/CD workflows.
- Experience working with distributed or big data processing technologies such as Apache Spark.
- Strong analytical thinking and problem-solving capabilities.
- Excellent communication and collaboration skills.
Preferred Qualifications
- Proficiency in Python for data engineering and automation tasks.
- Experience developing Spark applications using PySpark.
- Familiarity with file formats such as Parquet, Delta Lake, and Avro.
- Experience integrating data from APIs and external services.
- Understanding of Azure infrastructure concepts including subscriptions, resource groups, and permissions management.
- Experience using Git-based workflows for collaborative development.
- Familiarity with Azure DevOps pipelines and repository management.
- Exposure to infrastructure automation tools such as Ansible.
- Demonstrated ability to lead technical initiatives and work directly with business stakeholders.
- Adaptability and eagerness to learn emerging cloud and data technologies.
