Data Engineer (Offshore)
Role Overview We are looking for a strong, hands-on Data Engineer to drive technical execution across core data projects. In this role, you will work independently to architect, transform, and analyze complex datasets using Python, PySpark, and Databricks. You will be responsible for maintaining and delivering regular enhancements to our data pipelines, integrating digital analytics data, and ensuring reliable data delivery across the organization.
Key Qualifications
- Technical Proficiency: Strong, hands-on expertise in Python and PySpark for scalable data processing, transformation, and analysis.
- Platform Experience: Solid hands-on experience with Databricks for pipeline development, optimization, and workspace management.
- Domain Exposure: Familiarity or prior experience working with Google Analytics (GA4) web/app tracking data.
- API Development (Plus): Experience building RESTful microservices and data access APIs using FastAPI is a strong advantage.
- Soft Skills & Work Style: Highly independent self-starter with excellent problem-solving ability and fluent English communication skills to collaborate effectively with global team members and business stakeholders.
Key Responsibilities
1. Data Pipeline & Platform Engineering
- Design, build, and optimize scalable ETL/ELT pipelines using PySpark on the Databricks platform.
- Perform complex data transformations, data cleaning, and data modeling to support analytical and reporting needs.
- Ingest and process web/app tracking datasets, including Google Analytics integration pipelines.
2. System Maintenance & Regular Enhancements
- Maintain existing data pipelines, perform regular performance tuning, and execute continuous feature enhancements.
- Troubleshoot complex data errors, reduce latency, and ensure strict data quality across systems.
3. API & Data Access Delivery (Optional / Plus)
- Build and maintain high-performance APIs using FastAPI to expose structured data to downstream applications and services.
Core Competencies & Stack
- Programming & Processing: Python, PySpark, SQL
- Data Platform: Databricks
- Analytics Data: Google Analytics (GA4) / Digital Analytics
- API Frameworks: FastAPI (Nice-to-have)
- Delivery: Pipeline Optimization, Data Transformation, Performance Tuning
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