Data Engineer - Databricks

Zurich Insurance Company Ltd.•Ciudad de México, NM

16h•Remote

About The Position

Zurich Capability Center is currently hiring a Data Engineer with Databricks expertise. This role involves designing, building, and maintaining scalable data pipelines, developing and optimizing ETL/ELT processes, and implementing data ingestion frameworks. The Data Engineer will work closely with various teams to deliver reliable datasets, build data models, ensure data quality and security, and optimize Databricks environments. Additionally, the role supports the deployment of machine learning solutions and collaborates on CI/CD and DataOps best practices.

Requirements

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.
English level B2 or higher.

Nice To Haves

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.
Familiarity with MLflow and model deployment processes.
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.
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.

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.