[Hiring Week] Senior Data Engineer (GCP)

EPAM Systems; Malaysia; On-site; MYR 180,000 - 280,000; Full time

Job summary

EPAM Systems in Malaysia is seeking a Senior Data Engineer (Google Cloud Platform) to design and implement reliable ETL/ELT pipelines, optimize SQL, and orchestrate workflows with Airflow, turning raw data into ready-to-use datasets. You will partner with clients and delivery teams to improve quality, performance and operational stability across cloud data platforms.

You will work with BigQuery and cloud-native services on GCP and AWS, contributing to CI/CD improvements and robust data solutions

Qualifications

• ETL/ELT pipelines experience with data warehouses.
• Advanced SQL including optimization and validation.
• Python proficiency for pipeline development.
• Experience with distributed processing (PySpark or Apache Beam).
• Cloud workload experience on GCP and AWS.
• Experience with Airflow or Cloud Composer.
• Knowledge of data modeling and data quality controls.
• Clear communication to explain trade-offs and risks.

Responsibilities

• Design and build scalable ETL and ELT pipelines using Python, SQL, BigQuery and cloud-native services.
• Develop and optimize complex SQL for transformation, validation, troubleshooting and performance.
• Create and maintain data models and warehousing solutions that support quality, availability and scale.
• Orchestrate workflows in Apache Airflow, including scheduling, monitoring and incident resolution.
• Support pipeline delivery and platform operations across Google Cloud Platform and Amazon Web Services (AWS).
• Improve CI/CD, source control and automated deployment practices for data solution.
• Investigate data, integration and infrastructure issues, driving root-cause analysis and fixes.
• Collaborate with clients and cross-functional teams to clarify requirements, risks, dependencies and delivery plans.

Skills

ETL/ELT pipelines

Advanced SQL

Python

Airflow

Google Cloud Platform

AWS

PySpark

Apache Beam

Data modeling

Data quality controls

Communication

Tools

Airflow

PySpark

Apache Beam

BigQuery

Google Cloud Platform

AWS

Terraform

Kubernetes

Fivetran

Kafka

Job description

We are seeking a Senior Data Engineer (Google Cloud Platform). You will build reliable ETL and ELT pipelines, optimize SQL and orchestration in Apache Airflow and help teams turn raw data into trusted, ready-to-use datasets. You will partner with clients and delivery teams to improve quality, performance and operational stability across cloud data platforms.

Responsibilities

• Design and build scalable ETL and ELT pipelines using Python, SQL,Big Query and cloud-native services
• Develop and optimize complex SQL for transformation, validation, troubleshooting and performance
• Create and maintain data models and warehousing solutions that support quality, availability and scale
• Orchestrate workflows in Apache Airflow, including scheduling, monitoring and incident resolution
• Support pipeline delivery and platform operations across Google Cloud Platform and Amazon Web Services (AWS)
• Improve CI/CD, source control and automated deployment practices for data solution
• Investigate data, integration and infrastructure issues, driving root-cause analysis and fixes
• Collaborate with clients and cross-functional teams to clarify requirements, risks, dependencies and delivery plans

Requirements

• Hands-on experience building ETL and ELT pipelines and supporting data warehousing
• Advanced SQL skill set including optimization, data validation and complex transformation
• Python proficiency for pipeline development and software engineering practices
• Experience with distributed processing using PySpark or Apache Beam
• Practical cloud experience with Google Cloud Platform and or Amazon Web Services (AWS) for data workloads
• Workflow orchestration background with Apache Airflow or Google Cloud Composer
• Knowledge of data modeling data lifecycle management and data quality controls
• Clear communication with the ability to explain trade-offs, risks and solution options to stakeholders

Nice to have

• Infrastructure-as-code exposure using Terraform and or Kubernetes
• Streaming familiarity with Kafka and event-driven patterns
• Data integration tooling experience such as Fivetran