Data Engineering (Azure Databricks, Power BI, Python)

Mercedes-Benz Group

Kuala Lumpur

Remote

MYR 180,000 - 250,000

Full time

4 days ago

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Job summary

Mercedes-Benz Group in Kuala Lumpur is seeking a Senior Data Engineer / Data Engineering Lead to drive data and analytics initiatives within Sales Planning. You will lead end-to-end data engineering, design Azure-based data pipelines, and deliver Power BI solutions while coordinating with vendors and global teams.

The role combines hands-on engineering with technical leadership; you will assess requirements, define solutions, manage stakeholder expectations, and stay hands-on as needed.

Qualifications

Minimum 5-7+ years in Data Engineering/Analytics.
Hands-on with Azure stack: ADF, Databricks, Data Lake, Entra ID/AD, Key Vault.
Proficient in SQL and Python for data manipulation.
Proven Power BI report development experience.
Experience with GitHub, CI/CD, and Azure DevOps/GitHub Actions.
Familiar with Agile/Scrum and JIRA.
Strong stakeholder management and cross-functional coordination.

Responsibilities

Lead end-to-end data engineering and Power BI initiatives.
Design and maintain Azure-based data pipelines and data lake storage.
Develop and optimize data pipelines using SQL and Python.
Coordinate with vendors and global stakeholders.
Manage delivery with Azure DevOps or GitHub Actions.
Support API integrations and multiple data sources.
Provide hands-on guidance while mentoring the team.

Skills

Azure Databricks

Azure Data Factory

Azure Data Lake Storage

SQL

Python

Power BI

GitHub

Jira

Agile/Scrum

Stakeholder management

Leadership

Tools

Azure DevOps Pipelines

GitHub Actions

Databricks

Terraform

Job description

Tasks

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