Senior/Medior Data Engineer

Are you a motivated and innovative person, interested in driving strategic projects for one of the largest global insurers? Then this job is definitely something for you. The Data Engineer will be responsible for helping to power data-driven decisions and advancing the data and analytics tools of the Zurich organization. By leveraging new technology, the ZCAM (Zurich Customer Active Management) data engineering team ensures that all stakeholders in the organization can efficiently access reliable and accurate data. Data engineers develop, implement, and refine the standards, tools, and methodologies that make up the desired analysis environment within the organization. Their expertise helps create a strong data foundation within Zurich that keeps everyone informed and moving forward. What You Will Do - Design, build and maintain scalable batch data pipelines that extract, transform and load data from structured and unstructured sources - Develop and optimize data processing workloads using Spark on Databricks - Implement data cleansing, validation and quality checks to ensure downstream consumers can rely on accurate, consistent data - Write and tune advanced SQL, and optimize data models and data retrieval for performance and cost efficiency - Monitor pipelines and environments, troubleshoot issues and continuously improve observability and alerting - Lead data engineering projects from scoping through to delivery, working closely with technical and business stakeholders - Mentor junior and mid-level engineers through code reviews, pair programming and knowledge sharing - Evaluate and recommend new tools and technologies, and contribute to architectural decisions for the data platform - Represent the data team in technical and business meetings, reporting on progress, outcomes and priorities What You Bring - 5+ years of experience in data engineering or a closely related field (or 3-4 years with clear senior-level ownership), plus a degree in Computer Science, Informatics, Natural Sciences or equivalent practical experience - Strong Python skills with solid software engineering practices (OOP, testing, version control, CI/CD), and advanced SQL, including query and data model optimization - Production experience with Spark and Databricks in the Azure ecosystem (e.g. Data Factory, Synapse), orchestration tools such as Airflow, and a solid grasp of data modelling, warehousing and Lakehouse concepts - Proven track record of delivering data projects, a structured approach to problem solving, and the ability to explain technical topics clearly to both technical and non-technical stakeholders - Fluent Slovenian and English, written and spoken You belong here. This position is located in Slovenia within the Zurich Customer Active Management (ZCAM) team. At ZCAM, we are passionate about innovation and data-driven solutions. Join us and grow through access to learning resources, on-the-job development and continuous empowerment and support. Be part of a forward-thinking team that is creating a brighter future together. About Us Zurich is a leading multi-line insurer, serving over 75 million customers in more than 200 countries and territories with around 63,000 employees. For over 150 years, Zurich has been transforming insurance – offering not just protection, but also prevention services that promote well-being and climate resilience. Guided by our purpose to ‘create a brighter future together,’ we aim to be one of the most responsible and impactful businesses in the world. We look forward to receiving your online application today! Why Zurich At Zurich, we like to think outside the box and challenge the status quo. We take an optimistic approach by focusing on the positives and constantly asking What can go right? We are an equal opportunity employer who knows that each employee is unique - that’s what makes our team so great! Join us as we constantly explore new ways to protect our customers and the planet. - Location(s): SI - Ljubljana - Remote working: - Schedule: Full Time - Recruiter name: Vesna Pivk