Data Engineer - Databricks

Responsibilities

Design, build, and maintain scalable data pipelines using Databricks and cloud-based data platforms.

Develop, optimize, and automate ETL/ELT processes to support analytics, reporting, and machine learning initiatives.

Work closely with Data Scientists, Analysts, ML Engineers, and business stakeholders to understand data requirements and deliver reliable datasets.

Implement data ingestion frameworks from multiple structured and unstructured data sources.

Build and maintain data models, data lakes, and data warehouses that support enterprise analytics needs.

Ensure data quality, consistency, governance, and security across platforms.

Optimize Spark workloads and Databricks environments for performance and cost efficiency.

Support deployment and operationalization of machine learning solutions by providing production-ready datasets and feature pipelines.

Collaborate with Azure, IT, and DevOps teams to implement CI/CD and DataOps best practices.

Monitor, troubleshoot, and continuously improve data platform performance and reliability.

Skills and Experience

• Required
• Bachelor's Degree in Computer Science, Engineering, Information Systems, Mathematics, or a related field.
• 3+ years of experience in Data Engineering, Data Warehousing, or Big Data environments.
• Strong programming skills in Python and SQL.
• Hands-on experience with Databricks, Apache Spark, and distributed data processing.
• Experience designing and developing ETL/ELT data pipelines.
• Experience working with Data Lakes and modern data architectures.
• Understanding of data modeling concepts including Star Schema and Dimensional Modeling.
• Experience working with Git and version control systems.
• Strong analytical and problem-solving skills.
• Preferred Qualifications
• Experience with Azure Data Platform services, including:
• Azure Databricks
• Azure Data Factory
• Azure Data Lake Storage
• Azure Synapse Analytics
• Azure DevOps
• Experience working with Delta Lake and Lakehouse architecture.
• Knowledge of orchestration tools such as Airflow, Databricks Workflows, or Azure Data Factory.
• Experience supporting Machine Learning use cases and MLOps practices.
• Knowledge of CI/CD, Infrastructure as Code, and DataOps practices.
• Experience with streaming technologies such as Kafka or Event Hubs.
• Experience working in Agile environments.
• Insurance industry experience is a plus.
• Nice to Have
• Experience collaborating with Data Science teams and supporting AI/ML initiatives.
• Knowledge of Generative AI, LLM data pipelines, vector databases, and embedding workflows.
• Experience with Unity Catalog, data governance, and metadata management.
• Exposure to cloud-native architectures and enterprise-scale data platforms.

Who we are

Looking for a challenging and inspiring work environment where you can make a difference? At Zurich millions of individuals and businesses place their trust in our products and services every day. Our 53,000 employees worldwide form the basis of our success, enabling, businesses and communities to face a world of risk with confidence. Imagine if you could help people do this all over the world. You’d give them confidence and reassurance by protecting what they love most. It’s a big challenge, but you will be supported by a world-class team who believe in helping you to reach your full potential and deliver on our promises.

So be challenged. Be inspired. Help us make a difference.

At Zurich we are an equal opportunity employer. We attract and retain the best qualified individuals available, without regard to race/ethnicity, religion, gender, sexual orientation, age, or disability.