Senior Data Engineer (Azure | Databricks | Power BI)

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 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

• 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.
• Azure Synapse Analytics (nice to have)
• GitHub Actions
• Databricks Workflows
• Unity Catalog (nice to have)
• Hive Metastore (nice to have)
• Power BI
• DAX
• Data Analytics and Reporting
• CI/CD
• Docker
• Terraform (nice to have)
• Databricks CLI / Azure CLI (nice to have)

Nice to Have

• FastAPI
• Redis
• NATS
• PowerShell / Bash

Disclaimer: Please note that this position may be offered under a third-party employment arrangement, subject to the final hiring and engagement model. Regardless of the employment arrangement, the selected candidate will be assigned to support and work closely with Mercedes-Benz Malaysia, following Mercedes-Benz's project requirements and day-to-day operations.