Senior/Medior Data Engineer

Zurich Insurance

. Design, build, and maintain scalable batch data pipelines from structured and unstructured sources .

Posted 10/22/2026full-timeLjubljana • SloveniaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable data pipelines, optimizing data processing workloads using Spark and Databricks, and implementing data quality checks. Proficient in advanced SQL and experienced in leading data engineering projects while collaborating with stakeholders and mentoring team members.

Highest-signal resume keywords

Data Pipeline DesignSpark and DatabricksAdvanced SQL OptimizationData Engineering LeadershipPython Programming

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringSQLPythonData ModellingData WarehousingData Lakehouse ConceptsCI/CDOOPTestingVersion Control

Soft Skills

Problem SolvingCommunicationMentoringCollaborationStakeholder Engagement

Tools & Technologies

DatabricksSparkAzure Data FactoryAzure SynapseAirflow

Industry Keywords

Data EngineeringBatch Data ProcessingData Quality ChecksData Platform ArchitectureTechnical Meetings

Tech Stack

Tools & technologies

AirflowAzurePythonSparkSQL

About the role

Key responsibilities & impact

Design, build, and maintain scalable batch data pipelines from structured and unstructured sources
Develop and optimize data processing workloads using Spark on Databricks
Implement data cleansing, validation, and quality checks
Write and tune advanced SQL and optimize data models and data retrieval for performance and cost efficiency
Monitor pipelines and environments, troubleshoot issues, and improve observability and alerting
Lead data engineering projects from scoping through delivery
Collaborate with technical and business stakeholders
Mentor junior and mid-level engineers through code reviews, pair programming, and knowledge sharing
Evaluate and recommend tools and technologies
Contribute to data-platform architectural decisions
Represent the data team in technical and business meetings and report on progress, outcomes, and priorities

Requirements

What you’ll need

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
Strong Python skills
Software engineering practices including OOP, testing, version control, and CI/CD
Advanced SQL, including query and data model optimization
Production experience with Spark and Databricks in the Azure ecosystem, such as Data Factory and Synapse
Experience with orchestration tools such as Airflow
Solid understanding of data modelling, warehousing, and Lakehouse concepts
Proven track record of delivering data projects
Structured approach to problem solving
Ability to explain technical topics clearly to technical and non-technical stakeholders
Fluent Slovenian and English, written and spoken

Benefits

Comp & perks

Access to learning resources
On-the-job development
Continuous empowerment and support
Equal opportunity employer