Big Data Platform Engineer

HCL Technologies Limited

Kuala Lumpur

On-site

MYR 180,000 - 300,000

Full time

11 hours ago
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Job summary

HCL Technologies Limited is seeking a highly motivated Big Data Platform Engineer to design, develop, and maintain scalable data processing platforms and pipelines in Kuala Lumpur.

You will apply Python, Apache Spark, SQL, and Linux-based tooling to build reliable, high-performance data solutions for enterprise analytics, while collaborating with Data Architects, Product Owners, and DevOps teams.

Qualifications

  • Strong Python programming skills and experience developing data pipelines.
  • Hands-on Spark (PySpark) experience and SQL optimization.
  • Experience with Linux-based environments and DevOps practices.
  • Proficiency with Apache Airflow for workflow orchestration.
  • Container orchestration with Kubernetes (AKS/SKE) and cloud storage (MinIO/S3).

Responsibilities

  • Design, develop, and maintain scalable data pipelines using Python and Apache Spark.
  • Implement ETL/ELT processes for large-scale datasets.
  • Develop and optimize SQL queries and data models.
  • Ensure data quality, integrity, and reliability across the platform.

Skills

Python
Apache Spark (PySpark)
SQL
Linux
DevOps practices
Airflow
Kubernetes
MinIO / S3 Compatible
ETL/ELT
Git
Agile/Scrum
CI/CD pipelines
Shell scripting
Docker
Cloud platforms (Azure/AWS)
Distributed computing

Tools

Apache Spark
Azure/AWS
Docker
Kubernetes
Airflow
Git
MinIO / S3
AKS/SKE

Job description

We are seeking a highly motivated and skilled Big Data Platform Engineer to design, develop, and maintain scalable data processing platforms and pipelines. The ideal candidate should have strong expertise in Python, Apache Spark, SQL, and experience working in Linux-based environments with exposure to DevOps practices. The role involves building reliable, high-performance data solutions that support enterprise-scale analytics and business-critical applications.

Key Responsibilities
  • Design, develop, and maintain scalable data pipelines using Python and Apache Spark.
  • Implement efficient ETL/ELT processes for large-scale structured and unstructured datasets.
  • Develop and optimize complex SQL queries, data models, and transformations.
  • Ensure data quality, integrity, and reliability across the platform.
Platform Operations
  • Work with Linux-based environments for deployment, troubleshooting, and performance tuning.
  • Develop and maintain shell scripts for automation and operational tasks.
  • Monitor and optimize Spark jobs for performance, scalability, and resource utilization.
DevOps & Automation
  • Implement CI/CD pipelines and deployment automation.
  • Participate in infrastructure provisioning, monitoring, and release management activities.
  • Collaborate with DevOps teams to improve platform reliability and operational efficiency.
  • Work closely with Data Architects, Product Owners, and Business Stakeholders.
  • Participate in code reviews and ensure adherence to engineering best practices.
  • Create and maintain technical documentation and operational runbooks.
Mandatory Skills
Core Big Data Platform Skills
  • Strong programming experience in Python
  • Hands-on expertise with Apache Spark (PySpark preferred)
  • Strong SQL development and query optimization skills
  • Apache Airflow for workflow orchestration and scheduling
  • Kubernetes (AKS/SKE) for container orchestration and deployment. AKS/EKS/GKE also fine.
  • MinIO / S3 Compatible Object Storage like AWS S3 or other S3-compatible object storage experience
  • ETL/ELT Processing
  • Performance Tuning
  • Version Control (Git)
  • Agile/Scrum Delivery Model
Good to Have Skills
  • Shell Scripting (Bash/KSH)
  • Understanding of DevOps practices and CI/CD pipelines
  • Docker and Containerization Concepts
  • Cloud Platform Experience (Azure/AWS)
Desired Experience
  • 6 to 8 years of experience or 8 to 12 years or 12+ years of experience in Data Engineering or Big Data Platform Development.
  • Experience working with enterprise-scale data platforms.
  • Experience in distributed computing environments.
  • Strong analytical and problem-solving skills.
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