Data Engineer

About Us

Mercedes-Benz Tech Malaysia (MBTMY), established in 2003, is a global technology hub within the Mercedes-Benz Group. We play a key role in the company's digital transformation by delivering innovative digital solutions across the entire value chain.

With over 300 technology professionals, MBTMY contributes to a wide range of areas including software engineering, data and analytics, cybersecurity, cloud infrastructure, DevOps and artificial intelligence. From enhancing in-car digital experiences to improving global vehicle sales platforms and advancing AI and security initiatives, our teams help drive high-impact technology solutions for Mercedes-Benz worldwide. Our culture is built on agility, collaboration and continuous learning.

We provide an environment where innovation can flourish, supported by strong technical leadership, cross-functional teamwork and a shared commitment to quality and excellence. We also offer flexible hybrid work arrangements, allowing team members to balance remote work with in-person collaboration at our vibrant Wisma Mercedes-Benz office in Puchong. A space designed to inspire creativity, innovation and meaningful connection.

Job Description

• Design, develop, and maintain scalable Data Engineering solutions on Microsoft Azure.
• Build and optimize data pipelines using Azure Databricks, Azure Data Factory and Azure Data Lake Storage.
• Develop robust ETL/ELT pipelines to process structured, semi-structured and unstructured datasets.
• Implement data models, data quality frameworks and governance controls to support enterprise analytics and reporting.
• Collaborate with business stakeholders, analysts and product teams to understand requirements and translate them into scalable technical solutions.
• Develop and maintain Power BI datasets, reporting layers and analytical data products.
• Build and support CI/CD pipelines using Azure DevOps and GitHub.
• Monitor, troubleshoot and optimize data platform performance, reliability and scalability.
• Implement security best practices including Azure Key Vault integration, role-based access controls and data governance standards.
• Contribute to system architecture design, documentation and technical knowledge sharing.
• You build it, you test it, you run it.

Qualifications

• Minimum 5 years of working experience in Data Engineering, Data Platform Engineering or related fields.
• For senior positions, minimum 7 to 10 years of relevant experience preferred.
• Degree in Computer Science, Information Technology, Data Engineering, Data Science or related discipline.

Experience

• Experience working in Agile/Scrum environments.
• Experience with Azure Data Platform technologies.
• Experience developing enterprise-grade ETL/ELT pipelines.
• Experience supporting data warehouse, data lake and analytics platforms.
• Experience working with source control tools such as GitHub or Azure Repos.
• Experience with Jira and Confluence.

Specific Knowledge / Skills

• Strong analytical and problem-solving skills.
• Passionate about improving data quality, platform reliability and scalability.
• Strong stakeholder management and communication skills.
• Ability to work independently while collaborating across multiple teams.
• Product-oriented and results-driven mindset.

Knowledge and Skills

Data Engineering

• Strong SQL and Python/PySpark development.
• Experience building and supporting ETL/ELT pipelines.
• Data modelling experience including Star Schema, Snowflake Schema and Medallion Architecture.
• Experience with batch and streaming data processing.
• Experience developing data quality, validation and monitoring frameworks.

Cloud & Platform

• Microsoft Azure
• Azure Databricks
• Azure Data Factory
• Azure Data Lake Storage (ADLS)
• Azure Synapse Analytics (nice to have)
• Azure Key Vault
• Azure DevOps Pipelines
• GitHub Actions

Databricks & Big Data

• Apache Spark / PySpark
• Delta Lake
• Databricks Workflows
• Unity Catalog (nice to have)
• Hive Metastore (nice to have)

Visualization & Reporting

• Power BI
• DAX
• Data Analytics and Reporting

DevOps & Engineering

• GitHub / Azure Repos
• CI/CD
• Docker
• Terraform (nice to have)
• Databricks CLI / Azure CLI (nice to have)

Nice to Have

• FastAPI
• Redis
• NATS
• Kusto Query Language (KQL)
• Azure Log Analytics
• PowerShell / Bash

Disclaimer: This posting is for multiple project opportunities. Depending on project requirements, the role may be offered as direct employment or as an external contractor position under our partnered agencies. Contract type will be determined based on project needs.