Job Summary
About the Role We are looking for a passionate and skilled data engineer to join the Production Manufacturing data domain within Volvo Group Digital & IT. You will design, build, and optimize data pipelines and contribute to the development of scalable data products that support critical production and manufacturing operations. This role is hands-on, highly collaborative, and ideal for someone who enjoys turning complex data challenges into reliable, production-grade solutions. Key Responsibilities Design, develop, and optimize data pipelines and workflows using Azure Databricks and Python. Implement and maintain data solutions across the Azure Data Platform (Data Lake, Data Factory, Databricks, etc.). Develop and maintain APIs supporting data ingestion, data sharing, and interoperability. Collaborate closely with business stakeholders to gather requirements and translate them into technical solutions. Ensure data quality, security, and compliance across all solutions. Integrate data solutions into existing business processes and cross-functional systems. Continuously improve performance, cost-efficiency, and scalability of data systems. Required Skills & Qualifications Strong expertise in Azure Databricks, Python, and Spark (must-have). Solid experience with Azure Data Services, such as:Azure Data Lake and Azure Data Factory Experience in ingestion tools like: Qlik Recplicate / MQ / MQCC Experience with API development (REST/JSON or equivalent). Solid understanding of ETL processes, data modeling, and fundamental data architecture principles. Familiarity with CI/CD pipelines and version control (Git, etc.). Strong problem‑solving skills and structured way of working within an agile delivery model. Excellent communication and collaboration skills - you enjoy interacting with business stakeholders and cross-functional teams. Nice-to-Have Skills Experience with big data processing and performance tuning in Spark. Knowledge of data governance, lineage, and security best practices. Exposure to Power BI or similar visualization tools.
Key Responsibilities
About the Role We are looking for a passionate and skilled data engineer to join the Production Manufacturing data domain within Volvo Group Digital & IT. You will design, build, and optimize data pipelines and contribute to the development of scalable data products that support critical production and manufacturing operations. This role is hands-on, highly collaborative, and ideal for someone who enjoys turning complex data challenges into reliable, production-grade solutions. Key Responsibilities Design, develop, and optimize data pipelines and workflows using Azure Databricks and Python. Implement and maintain data solutions across the Azure Data Platform (Data Lake, Data Factory, Databricks, etc.). Develop and maintain APIs supporting data ingestion, data sharing, and interoperability. Collaborate closely with business stakeholders to gather requirements and translate them into technical solutions. Ensure data quality, security, and compliance across all solutions. Integrate data solutions into existing business processes and cross-functional systems. Continuously improve performance, cost-efficiency, and scalability of data systems. Required Skills & Qualifications Strong expertise in Azure Databricks, Python, and Spark (must-have). Solid experience with Azure Data Services, such as:Azure Data Lake and Azure Data Factory Experience in ingestion tools like: Qlik Recplicate / MQ / MQCC Experience with API development (REST/JSON or equivalent). Solid understanding of ETL processes, data modeling, and fundamental data architecture principles. Familiarity with CI/CD pipelines and version control (Git, etc.). Strong problem‑solving skills and structured way of working within an agile delivery model. Excellent communication and collaboration skills - you enjoy interacting with business stakeholders and cross-functional teams. Nice-to-Have Skills Experience with big data processing and performance tuning in Spark. Knowledge of data governance, lineage, and security best practices. Exposure to Power BI or similar visualization tools.