Senior Data Engineer - Data Products & Lakehouse Architect

Ascendion; Makati; On-site; PHP 1,000,000 - 1,500,000; Full time

Job summary

Ascendion is seeking a data engineering professional to design, build, and support data integration pipelines and analytical assets for a risk-focused datamart. You will onboard new data domains and enable governed data consumption across reporting, analytics, and decision-support use cases.

You will craft reusable data products, develop Airflow DAGs, PySpark scripts, and manage data quality controls, partnering with analysts and stakeholders to deliver scalable data platforms on AWS.

Qualifications

• Experience building enterprise data pipelines and analytical data products.
• Experience with data warehouses, data lakes, data marts, and reporting platforms.
• Experience integrating assets into a standardized architecture.

Responsibilities

• Develop and maintain data ingestion, transformation, and data quality pipelines.
• Analyze and enhance existing data marts, analytical datasets, and reporting assets to improve data usability, consistency, and scalability.
• Build reusable data products, views, and curated datasets for enterprise consumption.
• Implement reconciliation, monitoring, audit, and data quality controls.
• Optimize data processing workflows and query performance.
• Support data platform modernization initiatives, including migration and rationalization of existing analytical assets.
• Collaborate with business analysts, architects, and stakeholders throughout solution delivery.
• Support testing, deployment, operationalization, and production support activities.

Skills

Python

PySpark

SQL

Airflow/MWAA

AWS services

Data modeling

Git and CI/CD

Data quality

Job description

Ascendion is seeking a data engineering professional to design, build, and support data integration pipelines and analytical assets for a risk-focused datamart. You will onboard new data domains and enable governed data consumption across reporting, analytics, and decision-support use cases.

You will craft reusable data products, develop Airflow DAGs, PySpark scripts, and manage data quality controls, partnering with analysts and stakeholders to deliver scalable data platforms on AWS.