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Senior Data Engineer (Azure | Databricks | Power BI)

Mercedes-Benz Malaysia
Posted 6 hours ago
🇲🇾Malaysia🏢Hybrid📁Data & Analytics
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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: 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.


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