Data Engineer: Build Scalable Pipelines & Cloud Data Lakes

Stratpoint Technologies Inc.; Mandaluyong; Hybrid; PHP 900,000 - 1,500,000; Full time

Benefits offered by this job

Hybrid work model

Startup-like environment with strong治理

Job summary

Stratpoint Technologies Inc. is seeking a Data Engineer to design, build, and manage scalable data pipelines and architectures that feed databases, data lakes, and warehouses. You will optimize data flows from diverse sources for analytics and decision-making, leveraging Python/PySpark, SQL, and cloud services.

The role emphasizes strong software engineering, big data processing frameworks, and the ability to scale large data systems. Hybrid work is offered with collaborative IT governance.

Qualifications

• Bachelor’s degree in a relevant IT field.
• Strong software engineering background.
• Experience with data processing frameworks and large-scale data systems.
• Proficiency in Python / PySpark and SQL.
• Familiarity with cloud platforms (AWS, Azure) and data tooling.

Responsibilities

• Design, build, and maintain scalable data pipelines from multiple sources to databases, data lakes, or warehouses.
• Implement ETL/ELT processes for data collection, cleaning, and transformation.
• Collaborate with data teams to deliver clean, reliable data solutions for analytics.
• Manage cloud infrastructure and optimize for performance, cost, and scalability.
• Document architectures and provide tech support to IT and business partners.

Skills

Software engineering

Data processing frameworks

Scalability optimization

Python / PySpark

Education

Bachelor’s degree in Computer Engineering / Data Science / Statistics / Physics

Tools

Github

Databricks

AWS

PowerBI

Linux

Job description

Stratpoint Technologies Inc. is seeking a Data Engineer to design, build, and manage scalable data pipelines and architectures that feed databases, data lakes, and warehouses. You will optimize data flows from diverse sources for analytics and decision-making, leveraging Python/PySpark, SQL, and cloud services.

The role emphasizes strong software engineering, big data processing frameworks, and the ability to scale large data systems. Hybrid work is offered with collaborative IT governance.