Data Engineer (f/m/x)

Mercedes-Benz.io GmbH; Lisboa; Hybrid; EUR 55,000 - 75,000; Full time

Benefits offered by this job

Health insurance

Life insurance

Open source software

Flexible hybrid work model

International trainings and conference

Job summary

Mercedes-Benz.io is seeking a Data Engineer to build and maintain data pipelines powering analytics and decision-making across the organization. You will design scalable data infrastructure, work with Spark and Azure services, and collaborate with analysts to ensure high-quality data for reporting and ML workloads.

You will contribute to governance, monitoring, and production deployment while advancing platform performance and reliability in a fast-paced, hybrid environment.

Qualifications

• 3-5 years of hands-on software engineering experience building, maintaining, and optimizing data pipelines.
• Experience with OOP, TDD, CI/CD and version control practices.
• Strong PySpark and SQL proficiency with knowledge of Spark internals.
• Strong Python skills for data processing, automation and scalable pipelines.
• Expertise with Azure cloud tech: Databricks, Data Factory, Azure DevOps, Data Lake Storage.
• Solid experience in dimensional data modelling and data warehousing.
• Strong analytical and problem-solving skills; able to troubleshoot data challenges.
• Excellent communication and ability to work with technical and non-technical stakeholders.
• Collaborative mindset; thrive in fast-paced team environments.

Responsibilities

• Design and build scalable data pipelines for cleaning, integrating, and transforming large datasets.
• Create data processing infrastructure ensuring high-quality data availability for analysts and data scientists.
• Leverage Azure services including Data Factory, Databricks, and Data Lake Storage to build robust data solutions.
• Develop dimensional data models and maintain data warehousing for analytics and reporting needs.
• Write efficient Python and SQL code for large-scale data processing.
• Work with Apache Spark to develop and optimize PySpark code and SQL queries.
• Collaborate with data analysts and stakeholders to understand business requirements.
• Ensure data governance by monitoring data quality and implementing best practices.
• Support deployment, monitoring, and maintenance of ML pipelines and data solutions in production.
• Continuously improve platform performance, scalability, and reliability through automation.

Skills

3-5 years exp

OOP/TDD/CI-CD

PySpark

Python

Azure Databricks

Data Factory

Data Lake Storage

Dimensional modelling

Analytical skills

Communication

Collaboration

Tools

Kubernetes

Docker

Job description

HEY THERE!
We are Mercedes-Benz.io. Our mission is to ignite and build digital solutions for Mercedes-Benz by bringing together a tribe of digital enthusiasts who drive the digital future of mobility.

We believe flexibility and collaboration go hand in hand. With offices in Lisbon and Braga, we offer a flexible hybrid setup, with an average of one day per week in the office. This allows for meaningful in-person collaboration while maintaining the flexibility to work in a way that best supports you and your team.

We do not care about your shoes, as long as you bring the right attitude. At Mercedes-Benz.io we walk the talk and make things happen. We do not digitise for the sake of being digital, but to create real value. We reflect, challenge the status quo, and stand up for each other. This is why we hire people who want to make an impact.

WHAT IS PLATFORM & DATA

Focuses on building and evolving the technological and data‑driven foundation to enable scalable, efficient, and high‑quality digital products across the organisation. You would be part of the DOH - The Data Operations Hub drives the transformation towards a unified and efficient data ecosystem for Mercedes-Benz Digital Marketing and Sales.

As a Data Engineer within DOH, you will play a key role in building and maintaining the data foundations that power analytics, reporting, and data-driven decision-making across Mercedes-Benz.

IN THIS ROLE YOU WILL

• Design and build scalable data pipelines for cleaning, integrating, and transforming large datasets.

• Create data processing infrastructure that ensures high-quality data availability for digital analysts and data scientists.

• Leverage Azure cloud services including Data Factory, Databricks, and Data Lake Storage to develop robust and scalable data solutions.

• Develop dimensional data models and maintain data warehousing solutions that support analytics and reporting needs.

• Write efficient and well-tested Python and SQL code for large-scale data processing.

• Work extensively with Apache Spark developing and optimizing PySpark code and SQL queries while applying a deep understanding of Spark internals.

• Collaborate closely with data analysts and stakeholders to understand business requirements and support data-driven decision-making.

• Ensure data governance standards are met by monitoring data quality and implementing best practices for data management.

• Support the deployment, monitoring, and maintenance of machine learning pipelines and data solutions in production environments.

• Continuously improve platform performance, scalability, and reliability through automation and engineering best practices.

TO SUCCEED YOU NEED

• 3 to 5 years of hands-on software engineering experience building, maintaining, and optimizing data pipelines.

• Strong experience applying software engineering best practices, including object-oriented programming (OOP), test-driven development (TDD), CI/CD and version control.

• Proficiency in PySpark and SQL including query optimization and a solid understanding of Spark internals.

• Strong Python programming skills for data processing, automation, and scalable data engineering solutions.

• Proven expertise with Azure cloud technologies, including Databricks, Data Factory, Azure DevOps, and Data Lake Storage.

• Solid experience in dimensional data modelling and data warehousing principles.

• Strong analytical and problem-solving skills, with the ability to troubleshoot complex data challenges.

• Excellent communication skills and the ability to work effectively with technical and non-technical stakeholders.

• A collaborative mindset and the ability to thrive in a fast‑paced, team‑oriented environment.

THERE WILL BE BIG SMILES IF YOU HAVE

• Experience with Kubernetes and Docker for containerized applications.

• Experience working with Google Analytics data.

• Knowledge of machine learning deployment and monitoring practices.

• Experience working in large-scale cloud-based data platforms and modern analytics environments.

YOU WILL BE HAPPY WITH

• Flexible hybrid work model

• Open source software

• No top‑down hierarchy. We trust in your self‑organization

• Colleagues who are smart, driven, and collaborative

• An open‑minded and informal culture backed by a global brand

• Health insurance and life insurance

• Proactive self‑development through international trainings and conferences

• Much more cool stuff

THIS IS WHAT OUR PROCESS LOOKS LIKE

• Screening Call with our recruiter

• Take home challenge (if applicable)

• Technical Interview

• Culture Interview

• Offer

WHAT YOU'LL NEED TO KNOW ABOUT US

Mercedes-Benz.io develops software and technology for the digital platforms of Mercedes-Benz. Our main products are the Mercedes-Benz Website worldwide, the e-commerce platform, digital services and aftersales solutions.

We have a fantastic team with people from all over the world. We encourage frequent collaboration and pairing across disciplines. English is the main working language.

Mercedes-Benz.io is an equal opportunities employer. We believe that diverse experiences and a broad collective perspective lead to a better company culture and better products.

Please send your resumé in English and PDF.