Senior Data Engineer - End-to-End Data System & Analytics

agapi Ho Chi Minh City Metropolitan Area
Relocation
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AI Summary

Lead end-to-end data system development, optimize Spark performance, design data models, and build complex reports. Requires 4+ years of experience in Data Engineering with strong SQL, Spark SQL, and PySpark skills.

Key Highlights
Build and operate end-to-end data system
Design and develop data pipelines from Bronze to Gold layer
Optimize Spark performance and build data quality frameworks
Design Gold and Diamond data models for analytics and reporting
Key Responsibilities
Build and operate the company’s end-to-end data system
Design and develop data pipelines from Bronze to Gold layer
Optimize Spark performance, including partitioning, Z-ordering, and compaction
Develop shared frameworks and reusable components
Understand business requirements and KPI definition
Design Gold and Diamond data models for analytical purposes
Build complex reports and transformations using SQL and PySpark
Implement standardized incremental and backfill workflows
Build and maintain Data Quality frameworks
Perform cross-table and cross-source data validation
Implement anomaly detection and alerting mechanism
Conduct root-cause analysis and reduce recurring data issues
Technical Skills Required
SQL Spark SQL PySpark
Benefits & Perks
Competitive Compensation
Comprehensive Benefits
Work-Life Balance
Top-Tier Equipment
Thriving Culture

Job Description


Relocation is required; the company will provide a relocation assistance package



Responsibilities: The candidate will be responsible for building and operating the company’s end-to-end data system, including


Track P – Pipeline & Platform

  • Design and develop data pipelines from Bronze to Silver to Gold layer
  • Build batch and streaming pipelines, handling late-arriving data, CDC (Change Data Capture), and schema.
  • Optimize Spark performance, including partitioning, Z-ordering, and compaction
  • Develop shared frameworks and reusable components (e.g., joins, utilities, data quality pre-checks


Track A – Analytics & Reporting

  • Understand business requirements and KPI definition
  • Design Gold and Diamond data models for analytical purpose
  • Build complex reports and transformations using SQL and PySpark
  • Implement standardized incremental and backfill workflows


Track R – Data Reliability & Monitoring

  • Build and maintain Data Quality frameworks (e.g., row count checks, schema validation, metric consistency
  • Perform cross-table and cross-source data validation
  • Implement anomaly detection and alerting mechanism
  • Conduct root-cause analysis and reduce recurring data issues


Requirement:

  • + 4 years of experience in Data Engineering or related roles
  • Strong proficiency in SQL, Spark SQL, and PySpark
  • Hands-on experience with Databricks/Spark environment
  • Solid understanding of data modeling concepts: fact/dimension tables, grain, star schema...
  • Strong analytical thinking and problem-solving skills, with the ability to troubleshoot pipeline issues and optimize data process


What we offer

  • Competitive Compensation: Enjoy a salary package tailored to your skills and experience, along with performance-based bonuses
  • Comprehensive Benefits: We support your well-being with allowances, and assistance with work visa process
  • Work-Life Balance: Unwind with generous holiday and New Year bonus
  • Top-Tier Equipment: Stay productive with the latest tools, including a MacBook and iPhone
  • Thriving Culture: Immerse yourself in a dynamic, inclusive work environment that fosters grown.

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