Descrição

Job Description

HEY THERE!

We are Mercedes-Benz.io. Our mission is to ignite and build the digital solutions for Mercedes-Benz by forming a tribe of digital enthusiasts that drive Mercedes-Benz digital future.

Therefore, we offer you flexibility! You can choose to work from our offices in Lisbon or Braga, or remotely from any location in Portugal. Nonetheless, our tribe is our beating heart so we often organize company events and gatherings to bring MB.ioneers together. While some are optional, we would require your presence for certain team events and/or occasions.

We don’t care about your shoes, as long as you are wearing the right attitude. At Mercedes-Benz.io we walk the talk and make things happen. We do not digitize for the sake of being digital but for a better tomorrow for our customers. That’s not our job; it’s our passion. Therefore, we love to reflect and challenge everything – the status quo, Mercedes-Benz, and ourselves. We share the same beliefs and stand up for each other and this is why we hire unique people to join our Tribe of digital enthusiasts.

WHAT IS CENTRAL OPS & SERVICES?

At the Central Operations and Services Area, we provide reliable cloud solutions and different technical services to enable Mercedes-Benz digital products to focus on their business purpose.

We build up cloud infrastructure and services such as CI/CD Tools, Monitoring & Logging solutions, and many more tools used by our software development teams. Besides just providing tools, our teams collaborate closely with the Software Development teams to ensure and increase developer satisfaction by optimizing the platform services.

The Teams within the Area enables e.g. Identity Access Management or coherent customer data handling for all users interacting with the digital touchpoints.

Our central Service Management Team provides a overarching service management model including processes and tools.

IN THIS ROLE YOU WILL

OneDNA creates a cutting-edge data platform for KPI reporting, data analyses, and data science for the digital business of Mercedes-Benz.io. We are responsible for building, maintaining, and enhancing comprehensive data models that covers relevant data sources for more efficient reporting and analysis of our stakeholders.

We define and maintain KPI frameworks to ensure governance and enforcement. Our team builds and maintains dashboards with a defined business impact for stakeholders based on an aligned style guides and offer trainings. We ensure an efficient data sharing process in eXtollo for our data models, including documentation.

• Our team also offers consulting and enablement around to our stakeholders and finally, we build data science use cases to support data-driven product development.
• Develop & Maintain Data Pipelines: Design, build, and optimize scalable and reliable data pipelines for cleaning, integrating, and transforming large datasets.
• Infrastructure Development: Create and maintain data processing infrastructure to ensure high-quality data supply for digital analysts and data scientists.
• Cloud Integration: Leverage Azure cloud services, including Data Factory, Databricks, and Datalake Storage, to deploy robust data solutions.
• Data Modelling: Develop dimensional data models and maintain data warehousing solutions to support analytics and reporting needs.
• Performance Optimization: Write efficient, maintainable, and well-tested Python and SQL code, ensuring optimal performance for large-scale datasets.
• Spark Expertise: Work with Apache Spark to write and optimize PySpark code and SQL queries, understanding Spark internals for maximum efficiency.
• Collaboration: Partner with data analysts, data scientists, and stakeholders to understand data requirements, ensure quality, and support data-driven decision-making.
• Governance & Quality: Ensure data governance, monitor data quality, and implement best practices for data management.
• Deployment & Monitoring: Support deployment and monitoring of machine learning pipelines and data solutions in production environments.

Job Requirements

• TO SUCCEED YOU NEED
• 4+ years of hands-on software engineering experience, developing and maintaining data pipelines.
• Strong experience with software engineering best practices (OOP, TDD, CI/CD, version control).
• Proficiency with PySpark and SQL, including the ability to optimize queries and understand Spark internals.
• Proficient in Python for data processing and automation tasks.
• Strong expertise with Azure cloud services, including Databricks, Data Factory, DevOps, and Datalake Storage.
• Solid experience in dimensional data modelling and data warehousing principles.
• Knowledge of Kubernetes and Docker for containerized applications.
• Experien

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