Senior Databricks Data Engineer

For our client Aurobay we are looking for a Senior Databricks Data Engineer. Aurobay develops and produces world-class hybrid engines and transmissions. With factories on two continents - Sweden and China - we're a pioneering global supplier of propulsion technology, development services and contract manufacturing. The Aurobay brand brings together over 9,000 dedicated and determined people that design, develop, and manufacture next-generation powertrain solutions for a global market. Aurobay is part of HORSE Powertrain Limited, a global leader in powertrain solutions. The Group has 19,000 employees, 17 plants and 5 R&D centers across three continents. We partner with OEM customers around the world and offer innovative solutions that can cater to up to 80% of the growing hybrid and combustion powertrain market, enabling a faster transition toward cleaner mobility. At Aurobay, we are committed to diversity and inclusion. We welcome applicants from all backgrounds and believe that different perspectives and experiences make for a stronger, more innovative company. About the Role As a Senior Data Engineer, you will use Databricks as a foundation to design, build, and enable scalable reporting, analytics, and AI-driven insights. You will ensure that business-critical data is reliable, secure, governed, and accessible for approved use across the organization. As part of the Enterprise Analytics & Insights Team, you will work closely with business stakeholders, analytics specialists, platform teams, and source-system owners to translate data needs into sustainable technical solutions. The Senior Data Engineer strengthens the organization’s data capabilities through robust architecture, integration, automation, and continuous improvement. Key Responsibilities - Design, develop, and maintain scalable data platforms and solutions using Databricks, including data lakes, lakehouses, data warehouses, enterprise data services, and ETL/ELT frameworks. - Build, optimize, and support ETL/ELT pipelines and data integration workflows, integrating and harmonizing data from ERP, HR, Finance, CRM, and other enterprise systems for analytics and business consumption. - Develop trusted and reusable data products through data modeling, metadata management, and data architecture practices while ensuring data quality, lineage, security, governance, privacy, and regulatory compliance. - Ensure reliable and efficient data operations through monitoring, testing, automation, performance tuning, cost optimization, and recovery practices. - Partner with business, analytics, and engineering teams to translate requirements into scalable technical solutions, while driving engineering excellence through documentation, mentoring, technical reviews, and continuous improvement. Skill requirements Knowledge: Advanced knowledge of data engineering principles, enterprise data architecture, data integration, and cloud-based data platforms Strong understanding of ETL/ELT patterns, batch and streaming concepts, orchestration, dependency management, and error handling. Advanced knowledge of SQL, data modelling, dimensional modelling, data warehousing, lakehouse concepts, and analytics-ready data design. Knowledge of data governance, quality, lineage, metadata, access control, privacy, retention, and secure data handling. Understanding of API-based integration, file-based exchange, database connectivity, and common enterprise source-system patterns. Knowledge of DevOps and DataOps practices, including version control, automated testing, CI/CD, infrastructure configuration, and release management. Familiarity with analytics, business intelligence, AI, and machine learning consumption requirements. Experience: Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field, or equivalent practical experience. 5+ years of experience in data engineering, data platform development, Databricks, integration engineering, or a comparable technical role, designing and delivering scalable cloud-based data solutions and enterprise data pipelines. Proven experience integrating data from multiple business domains and source systems into governed analytics platforms, supported by robust data models and structures for reporting, analytics, and advanced data use cases. Experience implementing and supporting production-grade data solutions, including data quality controls, monitoring, troubleshooting, operational support, and continuous improvement. Experience collaborating with business and technical stakeholders, conducting technical reviews, and supporting the development and mentoring of other engineers. Skills: Advanced SQL and strong programming or scripting capability for data transformation and automation. Strong hands-on capability with cloud data services, orchestration tools, distributed processing, and data storage technologies. Ability to design secure, reliable, maintainable, and cost-conscious data solutions. Strong analytical troubleshooting skills across complex data flows, dependencies, and platform components. Ability to translate business and analytical requirements into clear technical architecture and implementation choices. Strong documentation, stakeholder communication, collaboration, and technical facilitation skills. Proactive and structured way of working, with strong attention to quality, security, governance, and operational sustainability. Ability to work effectively in a cross-functional, international, and evolving enterprise environment. Start date: 2026-10-01 End date: 2027-02-28 with possibilty for extension Workload: Hours per week: up to 40. Remote work: up to 50% Location: Göteborg, Sweden Payment terms: 60 days Equipment: Bring your own device We offer continuously. That means that we sometimes remove the assignments before deadline. If you are interested we recommend that you apply immediately. PayExpress: We now offer a fast and smooth pa