Data Engineering (Azure Databricks, Power BI, Python)

About Us 

At Mercedes-Benz, we don’t just build cars, we create great software. We develop tomorrow’s mobility together in our product lines, pushing the digitization of the Mercedes-Benz Group AG forward. As a tech company, we are agile, innovative, and always keep our finger on the pulse of change. This is why inner source, FOSS, secure code, DevOps, infrastructure as code (IaC), data analytics, artificial intelligence, and many more are core components of our daily work.

IT is our passion, and we move toward a bright future, sometimes quickly, sometimes creatively but always together.

We believe in integrity, trust, and transparency as part of our flexible work culture, with a strong emphasis on teamwork and the learning process, making mistakes, and achieving continuous progress together in all products we create and develop within the Mercedes-Benz Group.

Our workplace is anywhere* with a fast connection whether remotely at home, at your favorite café, or at our integrated office at Wisma Mercedes-Benz, which comes with an LRT station at its doorstep, an al fresco cafeteria, ample greenspaces, and free parking.

 

About the Role

We are looking for an experienced Senior Data Engineer / Data Engineering Lead to join the Sales Planning (Car Sales) function and take a leading role in upcoming data and analytics initiatives.
 

This position combines hands-on data engineering with technical project leadership. The successful candidate will lead the end-to-end delivery of Power BI solutions and Azure-based data pipelines, while coordinating external vendors and working closely with business stakeholders and global teams.
 

The ideal candidate can independently assess technical requirements, define an appropriate solution approach, coordinate delivery, manage stakeholder expectations, and remain hands-on where required.

 

Key Responsibilities

• Lead the end-to-end delivery of data engineering, data pipeline and Power BI initiatives.
• Design, develop and maintain scalable solutions using Microsoft Azure, Azure Data Factory and Azure Databricks.
• Develop, optimize and support data pipelines using SQL and Python.
• Work with Azure Data Lake Storage for data storage, processing and integration requirements.
• Develop and enhance Power BI reports and dashboards based on business needs.
• Coordinate external vendors and provide technical direction for data engineering activities.
• Manage communication and expectations across business stakeholders, technical teams and global counterparts.
• Support integration requirements involving APIs and multiple data sources.
• Apply Azure DevOps Pipelines and/or GitHub Actions, including pipeline triggers and CI/CD concepts.
• Manage source code and collaborative development using GitHub.
• Work within an Agile/Scrum environment and manage delivery through JIRA.
• Support secure Azure implementations using Microsoft Entra ID and Azure Key Vault.
• Provide technical guidance while remaining hands-on with engineering and troubleshooting activities.

Qualifications 

Required

Must-Have Requirements

• 5-7+ years of experience in Data Engineering, Data Analytics, Data Platforms or a related technical environment.
• Strong hands-on experience with Microsoft Azure, Azure Databricks, Azure Data Factory, Azure Data Lake Storage, Microsoft Entra ID / Azure Active Directory, and Azure Key Vault.
• Strong programming and data manipulation skills using SQL and Python.
• Proven experience in Power BI report development.
• Experience using GitHub for source control and collaborative development.
• Understanding of Azure DevOps Pipelines and/or GitHub Actions, including triggers and CI/CD concepts.
• General understanding and practical experience working with APIs.
• Experience working within Agile/Scrum environments and using JIRA.
• Proven ability to lead technical projects and coordinate delivery across multiple parties.
• Strong stakeholder management skills across business, technical, vendor and global teams.
• Ability to work independently within a flat structure and with minimal supervision.

 

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