Data Platform Engineer

Private Advertiser; Kuala Lumpur; On-site; MYR 110,000 - 170,000; Full time

Job summary

Private Advertiser is seeking a Data Platform Engineer to improve the performance, scalability, reliability and cost efficiency of Azure, Snowflake and PostgreSQL workloads. You will enhance data processing, infrastructure, automation, observability and controlled changes, collaborating with data, streaming, platform operations, monitoring and security teams.

The role emphasizes optimisation, cost management, reusable IaC, and robust CI/CD pipelines with Azure DevOps.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, Data Engineering or a related field.
• 3+ years hands-on experience in Data Platform Engineering, Cloud Engineering or DevOps with platform responsibilities.
• Strong Python and SQL skills for automation and data processing.
• Practical Microsoft Azure experience across compute, storage, networking, identity, and environment configuration.
• Hands-on experience with Snowflake or PostgreSQL, including query troubleshooting 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.

Responsibilities

• Optimise performance and scalability of Azure, Snowflake, and PostgreSQL workloads.
• Analyse cloud consumption and cost drivers, recommend sizing and tuning.
• Develop reusable IaC modules with Terraform and enforce configuration drift detection.
• Build and improve CI/CD pipelines using Azure DevOps and Git.
• Improve SQL transformations and processing frameworks for maintainability and performance.
• Develop automation in Python, SQL and REST APIs for repeatable tasks.
• Implement monitoring-as-code and instrument systems for reliability and cost insight.
• Maintain engineering standards, templates, and runbooks; support knowledge transfer.
• Collaborate with European teams during CET business hours.

Skills

Python

SQL

DevOps

Data modeling

Troubleshooting

Education

Bachelor's degree in Computer Science

Tools

Azure DevOps

Terraform

dbt

Airflow

NiFi

Git

Job description

Join a data platform engineering team focused on improving the performance, scalability, reliability and cost efficiency of Microsoft Azure, Snowflake and PostgreSQL workloads. You will deliver engineering improvements across data processing, infrastructure, automation, observability and controlled change, while collaborating with data, streaming, platform operations, monitoring and security teams.

Key responsibilities

Optimise the performance and scalability of Azure, Snowflake and PostgreSQL workloads through query analysis, workload testing and capacity analysis.

Analyse cloud and data-platform consumption and cost drivers, recommending resource sizing, workload tuning and configuration improvements.

Develop reusable standards, templates and configuration patterns for batch, streaming and event-driven data workloads.

Build and improve CI/CD pipelines using Azure DevOps and Git, including automated testing, validation, environment promotion, release controls, rollback procedures and post-deployment checks.

Develop and maintain reusable infrastructure-as-code modules using Terraform or equivalent tooling, including configuration-drift detection, approved access controls and secure credential handling.

Improve SQL transformations, dbt models and processing frameworks for maintainability, performance, reuse and downstream compatibility.

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.

Investigate recurring technical issues, implement preventive fixes, and support regression testing, recovery and rollback validation.

Maintain an engineering improvement backlog 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.

Maintain engineering standards, reusable templates, design notes, deployment instructions and recovery runbooks, while participating in knowledge transfer.

What we're looking for

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

At least 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 and access, and environment configuration.

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

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 collaborate with European-based teams during Central European business hours and agreed critical periods.