Data Engineer | Mandaluyong (Hybrid)

Work Setup: Monday to Friday, Hybrid (2 days onsite, 3 days wfh)
Location: Mandaluyong

Key Responsibilities:

• Support the development and deployment of data pipelines for high-priority business requirements and product initiatives, working under the direction of senior team members.

• Monitor pipeline performance and availability, address routine data quality concerns within expected timelines, and escalate complex technical issues when necessary.

• Handle data-related requests and incidents within established service-level agreements (SLAs), ensuring workflows run properly through standard procedures, testing, and deployment practices.

• Keep pipeline documentation and test coverage up to date while following established practices for CI/CD, data validation, governance, and system monitoring.

• Work with cross-functional teams through technical discussions and knowledge-sharing sessions, providing timely updates on potential risks, challenges, and project blockers.

Qualifications:

• Bachelor’s degree in IT, Computer Science, Engineering, Mathematics, or a related field, with 2–3 years of experience in data, analytics, or software engineering.

• Proficient in Python for scripting and data processing, and SQL for querying, joining, filtering, and aggregating data.

• Hands-on experience building ETL/ELT pipelines using databases, data warehouses, cloud platforms (AWS preferred), and orchestration tools such as Airflow or Dagster.

• Familiarity with Git, Docker, dbt, Terraform, and database migration tools such as Alembic or Atlas.

• Skilled in writing maintainable code, documenting processes, implementing data quality checks, and testing, with a strong willingness to learn new technologies.