Data Engineer

Philippine Batteries Incorporated; Quezon City; On-site; PHP 600,000 - 1,200,000; Full time

Benefits offered by this job

Data engineering environment

Job summary

Philippine Batteries Incorporated is seeking a Data Engineer to build robust data pipelines and data models for analytics and Genie AI applications. The role focuses on scalable transformations, quality controls and production support in a fast-paced data environment.

You will own data lineage, orchestration and cost-aware design while enabling ML features and semantic layers for dashboards and insights.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, Statistics or a related field.
• Three or more years building production data pipelines; ML analytics workloads evident.
• Databricks or equivalent Lakehouse experience strongly preferred.

Responsibilities

• Build and maintain Bronze to Silver to Gold transformations and automated data-cleaning pipelines.
• Create aggregated tables that shorten the path from raw data to dashboards and Genie insights.
• Design reusable customer, product, location, asset, material, transaction and process models.
• Implement business rules, historical and slowly changing logic, reconciliations and data-quality controls.
• Build data-quality monitoring and publish quality metrics for certified datasets.
• Investigate and resolve data defects raised by consumers.
• Optimize storage, partitioning, compute, orchestration and cost.
• Implement testing, version control and CI/CD for pipelines.
• Support production pipelines, including on-call or scheduled support arrangements.
• Support feature pipelines for machine learning, forecast inputs, semantic layers, Genie Spaces and AI applications.
• Document lineage, definitions and refresh behaviour for every certified dataset.
• Certified datasets and reusable domain models.
• Tested, version-controlled and documented pipelines.
• Data-quality dashboards and control reports.
• Lineage and technical documentation.
• Performance and cost-optimization improvements.

Skills

Advanced SQL

Python

PySpark

Databricks

Delta Lake

Unity Catalog

Medallion Architecture

Orchestration

CI/CD

Data Modelling

Data Quality

Git

Production Ownership

Education

Bachelor's in CS/IT/Engineering

Tools

Databricks

Delta Lake

Unity Catalog

Medallion Architecture

Git

Job description

• Build and maintain Bronze to Silver to Gold transformations and automated data-cleaning pipelines.
• Create aggregated tables that shorten the path from raw data to dashboards and Genie insights.
• Design reusable customer, product, location, asset, material, transaction and process models.

Quality and correctness

• Implement business rules, historical and slowly changing logic, reconciliations and data-quality controls.
• Build data-quality monitoring and publish quality metrics for certified datasets.
• Investigate and resolve data defects raised by consumers.

Performance and operations

• Optimize storage, partitioning, compute, orchestration and cost.
• Implement testing, version control and CI/CD for pipelines.
• Support production pipelines, including on-call or scheduled support arrangements.

Enablement

• Support feature pipelines for machine learning, forecast inputs, semantic layers, Genie Spaces and AI applications.
• Document lineage, definitions and refresh behaviour for every certified dataset.
• Certified datasets and reusable domain models.
• Tested, version-controlled and documented pipelines.
• Data-quality dashboards and control reports.
• Lineage and technical documentation.
• Performance and cost-optimization improvements.

Accountability and Success Measures

• Correctness of data against source and business rules.
• Freshness and reliability of certified data products.
• Performance, cost efficiency and maintainability of pipelines.
• Completeness of lineage and documentation.
• Reproducibility — a result produced today can be reproduced tomorrow.

Working Relationships

• Internal: Systems Integration Engineers; BI & AI Context Engineers; Data Scientists; AI / LLM Engineers; Data Governance Specialist; Data & AI Translators; Data Engineering Capability Head.

QUALIFICATIONS

• Bachelor's degree in Computer Science, Information Technology, Engineering, Statistics or a related field.
• Three or more years building production data pipelines. Demonstrated delivery of dimensional or domain models serving analytics and machine learning workloads. Databricks or equivalent Lakehouse experience strongly preferred.

Technical Skills

• Advanced SQL and Python; PySpark.
• Databricks, Delta Lake, Unity Catalog and medallion architecture.
• Dimensional and domain data modelling.
• Orchestration and workflow scheduling.
• Data-quality frameworks and testing.
• Git, CI/CD and code review practice.
• Performance tuning and cost management.
• Rigor — will not ship a number that has not been reconciled.
• Systems thinking about downstream consumers.
• Ownership of production outcomes, not just code delivery.
• Constructive code review and knowledge sharing.
• Continuous improvement and automation instinct.