Databricks Data Engineer - ETL & Pipelines

DysrupIT Pty; Manila; On-site; PHP 700,000 - 1,300,000; Full time

Job summary

DysrupIT Pty is seeking a mid-level Data Engineer with hands-on experience in Databricks to support design, development, and optimization of scalable data solutions in Manila. You will work within cross-functional teams to translate data requirements into robust pipelines.

Responsibilities include building and maintaining ETL/ELT processes, working with structured and unstructured data, developing data models, ensuring data quality and governance, and collaborating with analysts and business

Qualifications

• Minimum 2+ years of experience in data engineering.
• Hands-on experience with Databricks.
• Strong proficiency in Python and/or SQL.
• Experience with data pipeline development and data transformation frameworks.
• Familiarity with cloud platforms (e.g., Azure, AWS, or GCP).
• Understanding of data warehousing concepts and modern data architectures.
• Experience with version control tools (e.g., Git).
• Strong problem-solving skills and attention to detail.

Responsibilities

• Design, develop, and maintain data pipelines using Databricks and related technologies.
• Build and optimize ETL/ELT processes for large-scale data processing.
• Work with structured and unstructured data across multiple data sources.
• Develop and manage data models to support analytics and reporting requirements.
• Collaborate with stakeholders including data analysts, developers, and business teams to understand data needs.
• Ensure data quality, integrity, and governance across data platforms.
• Monitor and troubleshoot data workflows and performance issues.

Job description

DysrupIT Pty is seeking a mid-level Data Engineer with hands-on experience in Databricks to support design, development, and optimization of scalable data solutions in Manila. You will work within cross-functional teams to translate data requirements into robust pipelines.

Responsibilities include building and maintaining ETL/ELT processes, working with structured and unstructured data, developing data models, ensuring data quality and governance, and collaborating with analysts and business