Data Engineer

Company description:
Who are we?Volvo Cars is a company on a mission; to bring traditional car manufacturing into a connected, sustainable and smart future.Since 1927, we have been a brand known for our commitment to safety, creating innovative cars that make life less complicated for our consumers. In 2010, we decided to transform our business, resulting in a totally new generation of cars and technologies, as well as steady growth and record sales. Today, we’re expanding our global footprint in Europe, China and the US, and we’re on the lookout for new talent. We are constantly pushing our own skills and abilities to drive change in the automobile industry like never before. We are looking for innovative, committed people to join us in this endeavour and create safe, sustainable and connected cars. We believe in the power of people and will challenge and support you to reach your full potential. Join us and be part of Volvo Cars’ journey into the future.
Job description: Let's introduce ourselves
Software engineering is an increasingly important area in the automotive industry. Volvo Cars is bringing more of the software development in-house to better handle continuous integration and the complex interactions between different functions. Our data vision at Volvo Cars is powering innovation and every decision with trusted data and manage obstacles through innovative, robust designs and design for change.
 
You can now join the Engineering Data Hub. Our ART mission is to provide trusted data and insights to understand product & process performance and customer behavior, enabling improved efficiency and better customer experience.
 
We are the Data Product Engineering team, working to accelerate and streamline the use of data, analytics, and AI. The team innovates and collaborates to provide crucial contextual data and vital APIs to both internal and external consumers. Within the Volvo Cars Engineering organization, we help people (and AI systems) orient themselves in a complex product landscape by providing the right context through well-structured data. As the product grows in complexity, so does the data—our job is to make that complexity usable by transforming it into reliable, discoverable datasets and APIs that power analytics, applications, and AI.
What you'll do
As a Software Developer, you will build a data-driven application that transforms complex product information into reliable, discoverable datasets and APIs. You will design and operate batch pipelines, real-time querying systems, or a combination of both—depending on the use case and business needs.
 
A fundamental challenge for us is combining large-scale data with low latency. We operate on massive datasets, while ensuring that consumers can access relevant subsets quickly and efficiently. We are in a crucial phase of the project, designing the next generation of our product. You will directly contribute to the design and development of core capabilities. You will also work with a composable data stack, selecting the right tools and patterns to deliver scalable, maintainable, and secure applications.
 
Some tools we use today
•    Languages: Python, Go, SQL•    Query engines: Spark, Postgres, DuckDB•    Events: Kafka•    Cloud infrastructure: Azure, Kubernetes•    DevOps: GitHub Actions, FluxCD, Helm, Prometheus, Grafana, Vault•    PaaS: Databricks, Snowflake
What you'll bring
We are looking for a proactive individual with a solution-oriented mindset who is proficient in the following areas:
•    Software development: Git-first mindset and a proven track record in languages such as Python, Go, Rust, or similar•    Cloud: Azure and Kubernetes•    Storage: Open table formats (Delta, Iceberg, Hudi)•    Cloud-native application development•    Query engines: Postgres, DuckDB, SparkSQL
We value a strong software engineering profile and the mindset that data engineering is fundamentally a software discipline. You are familiar with DevOps practices, as well as test- and specification-driven development. You have a proven track record of building, deploying, and maintaining production systems.
 
In addition, experience in any of the following is highly valued:•    Automotive or complex systems: Experience working with data from complex domains such as automotive, robotics, IoT, aerospace, or similar•    Large-scale data processing: Spark and SQL•    Developing data pipelines: Building reliable and resilient processing systems