Senior/Mid Data Engineer

About the role

Zurich's Customer Active Management (ZCAM) data engineering team in Ljubljana is looking for a Senior/Mid Data Engineer to help power data-driven decisions and advance the data and analytics tools of the organization. The team builds the standards, tools and methodologies that let all stakeholders access reliable and accurate data. The position is full time, hybrid and based in Slovenia.

Key responsibilities

• 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 so 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 to delivery, working 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.

Required profile

• 5+ years of experience in data engineering or a closely related field (or 3-4 years with clear senior-level ownership).
• Degree in Computer Science, Informatics, Natural Sciences or equivalent practical experience.
• Proven track record of delivering data projects, a structured approach to problem solving, and the ability to explain technical topics clearly to technical and non-technical audiences.
• Fluent written and spoken Slovenian and English.

Required skills

• Strong Python 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.
• Solid grasp of data modelling, warehousing and Lakehouse concepts.