Data Engineer (Azure Databricks)

EPAM Systems; Malaysia; On-site; MYR 80,000 - 130,000; Full time

Job summary

EPAM Systems in Malaysia is seeking a Data Engineer (Databricks) to build reliable pipelines and analytics-ready datasets on Azure for Power BI reporting and digital analytics use cases. You will take ownership from external vendors, improve stability and data quality, and partner with BI and product teams to keep data trusted and usable.

Responsibilities include building and maintaining ETL/ELT pipelines with Python, PySpark and SQL in Databricks, ingesting GA4 data, creating analytics-ready

Qualifications

• Databricks development using Python, PySpark and SQL.
• Azure data/analytics context experience.
• GA4 knowledge and data connections validation.
• Strong English communication.

Responsibilities

• Build and maintain ETL/ELT pipelines in Databricks using Python, PySpark and SQL.
• Ingest data from multiple sources including GA4 using reliable patterns.
• Create analytics-ready tables for Power BI dashboards and self-serve analysis.
• Design reporting-ready models including star schemas, facts, dimensions, grain and keys.
• Implement data quality controls including checks for accuracy, completeness, freshness and reconciliation.
• Operate pipelines end to end including monitoring, troubleshooting and backfills.
• Partner with BI developers, analysts and stakeholders to translate reporting needs into data structures.
• Lead knowledge transfer from external teams through documentation and handover planning.

Skills

Databricks

Python

PySpark

SQL

Azure

Data Modeling

Data Quality

English Communication

Job description

We are seeking a Data Engineer (Databricks). You’ll build reliable pipelines and analytics-ready datasets on Azure for Power BI reporting and digital analytics use cases. You will take ownership from an external vendor, improve stability and data quality and partner with BI and product teams to keep data trusted and usable.

Responsibilities

• Build and maintain ETL and ELT pipelines in Databricks using Python, PySpark and SQL
• Ingest data from multiple sources including Google Analytics (GA4) using reliable patterns
• Create curated, analytics-ready tables for Microsoft Power BI dashboards and self-serve analysis
• Design reporting-ready models including star schemas, facts, dimensions, grain and keys
• Implement data quality controls including checks for accuracy, completeness, freshness and reconciliation
• Operate pipelines end to end including monitoring, troubleshooting, backfills and performance tuning
• Partner with BI developers, analysts and stakeholders to translate reporting needs into data structures
• Lead knowledge transfer from external teams through documentation, stabilization and handover planning

Requirements

• Databricks development skill sets using Python, PySpark and SQL
• Data engineering background supporting analytics and business intelligence back ends
• Microsoft Azure experience in a data and analytics context
• Google Analytics (GA4) knowledge including metrics, dimensions and validating data connections
• Data modeling ability for reporting and consumption-layer design
• Knowledge of orchestration concepts, incremental loads and partitioning approaches
• Experience contributing to data quality practices and controls
• Clear communication in English
• No visa sponsorship is available for this role

Nice to have

• Google BigQuery experience including GA4 export datasets and cost-aware querying
• Familiarity validating Microsoft Power BI models and star schema compatibility
• Exposure to Azure Data Lake Storage Gen2 (ADLS Gen2), Azure Key Vault or CI/CD for data pipelines