Data Platform Engineer

北京汉克时代科技有限公司; Kuala Lumpur; On-site; MYR 90,000 - 140,000; Full time

Job summary

北京汉克时代科技有限公司 in Malaysia seeks a hands-on Data Platform Engineer to modernize a large-scale Azure-based data platform for a globally recognised football organisation. The role focuses on performance, automation, and scalable data processing across batch, streaming and event-driven workloads.

The ideal candidate has 3+ years in data platform engineering, strong Python/SQL skills and practical Azure, Snowflake or PostgreSQL experience.

Qualifications

• 3+ years of hands-on Data Platform Engineering or related role.
• Strong Python and SQL for automation and data processing.
• Hands-on Microsoft Azure experience across compute, storage, networking and identity.

Responsibilities

• Platform Performance & Scalability: optimize Azure, Snowflake and PostgreSQL workloads and analyze bottlenecks.
• Cloud Cost Optimization: identify cost drivers and tune resources for benefits without impacting performance.
• Engineering Standardization: develop reusable templates for ingestion, transformation and orchestration.
• CI/CD & Quality Automation: build/test and automate releases with traceability and rollback procedures.
• Infrastructure as Code: maintain Terraform modules and secure deployment credentials.
• Data Models & Processing Frameworks: enhance dbt models and processing pipelines for maintainability.
• Automation & Observability Engineering: automate tasks with Python/SQL and implement monitoring-as-code.
• Reliability & Controlled Change: prevent issues, support rollback validation and approved releases.
• Documentation & Collaboration: maintain design notes, runbooks and cross-team knowledge transfer.

Skills

Python

SQL

Azure

CI/CD

Terraform

dbt

Airflow

Snowflake

PostgreSQL

ETL/ELT

Git

Monitoring

Education

Bachelor's degree in Computer Science, Software Engineering, Information Technology, Data Engineering, or related field

Tools

Azure DevOps

Job description

Join an international engineering team supporting a globally recognised football organisation based in Europe. We are hiring a hands-on Data Platform Engineer to help modernise and continuously improve a large-scale enterprise data platform on Microsoft Azure as part of a long-term managed service engagement.

This is an opportunity to take ownership of practical engineering improvements across platform performance, cost efficiency, scalability and automation. You will build reusable standards, strengthen CI/CD and infrastructure as code, and enhance data models and processing frameworks.

You will collaborate with specialists across Malaysia, China, the US and Europe, working with technical leads, data engineering, operations and monitoring teams. We are looking for an engineer who can turn technical challenges into tested improvements and demonstrate measurable results.

Key responsibilities

Platform Performance & Scalability: Optimize the performance and scalability of Microsoft Azure, Snowflake and PostgreSQL workloads. Investigate query execution, processing bottlenecks and resource constraints, and validate improvements through workload testing and capacity analysis.

Cloud Cost Optimization: Analyse cloud and data-platform resource consumption and cost drivers. Recommend workload tuning, resource sizing and configuration improvements, and verify cost benefits alongside performance, reliability and data-quality requirements.

Engineering Standardization: Develop reusable standards, templates and configuration patterns for data ingestion, transformation and orchestration. Improve consistency in dependencies, error handling, data validation and deployment across batch, streaming and event-driven workloads.

CI/CD & Quality Automation: Build and improve CI/CD pipelines using Azure DevOps and Git. Automate testing, validation, environment promotion and release controls for data-platform code and configuration, with traceability, rollback procedures and post-deployment checks.

Infrastructure as Code: Develop and maintain reusable infrastructure-as-code modules using Terraform or equivalent tooling. Support consistent provisioning and environment configuration, configuration-drift detection, approved access controls and secure handling of deployment credentials.

Data Models & Processing Frameworks: Improve SQL transformations, dbt models and processing frameworks for maintainability, performance and reuse. Collaborate with data engineering and technical leads on model evolution, dependency management, data-quality tests and compatibility with downstream consumers.

Automation & Observability Engineering: Develop Python, SQL and REST API automation for repeatable engineering and operational tasks. Implement monitoring-as-code and instrumentation with the monitoring team, using performance, cost and reliability evidence to guide improvements.

Reliability & Controlled Change: Investigate recurring technical issues and implement preventive engineering fixes. Support regression testing, recovery and rollback validation, and deliver changes through approved release and change-management processes while preserving live-service stability.

Continuous Improvement & Innovation: Maintain a prioritized engineering improvement backlog with technical leads and service teams. Baseline and measure outcomes such as deployment reliability, release lead time, manual effort, processing performance and resource consumption. Evaluate approved tools and pilots through controlled technical assessments.

Documentation & Collaboration: Maintain engineering standards, reusable templates, design notes, deployment instructions and recovery runbooks. Participate in knowledge transfer and collaborate with data, streaming, platform operations, monitoring and security teams across delivery locations.

What we're looking for

Bachelor's degree in Computer Science, Software Engineering, Information Technology, Data Engineering, or a related field.

Minimum 3 years of hands-on experience in Data Platform Engineering, Cloud Engineering, DevOps, Data Engineering with platform responsibilities, or a related technical role.

Strong Python and SQL skills for automation, data processing, troubleshooting and performance improvement.

Practical Microsoft Azure experience covering compute, storage, networking, identity/access and environment configuration.

Hands-on Snowflake or PostgreSQL experience, including query troubleshooting, workload analysis and resource optimization.

Experience with CI/CD, Git, automated testing and controlled releases, using Azure DevOps or comparable tooling.

Practical Terraform or equivalent infrastructure-as-code experience, including reusable configuration and change validation.

Good understanding of ETL/ELT, data modelling and orchestration, with experience in dbt, Airflow, NiFi or equivalent tools.

Ability to diagnose root causes, implement tested changes and validate improvements against baselines while following access and security controls.

Strong problem-solving, collaboration and technical documentation skills, with ownership of assigned engineering improvements.

Fluent English and flexibility to work with European-based teams during Central European business hours and agreed critical periods.