Data Engineer - Databricks

Zurich Insurance; Región Centro; Presencial; MXN 860.289 - 1.204.404; Jornada completa

Descripción de la vacante

Zurich Insurance is hiring a Data Engineer - Databricks in Mexico City. The successful candidate will design and build scalable data pipelines, develop ETL processes, and collaborate with Data Scientists and other stakeholders. A Bachelor's degree and 3+ years of experience in Data Engineering are required.

Candidates should possess strong programming skills, particularly in Python and SQL, and have hands-on experience with Databricks and Apache Spark. Knowledge of Azure services is preferred.

Formación

• 3+ years of experience in Data Engineering, Data Warehousing, or Big Data environments.
• Hands-on experience with Databricks and Apache Spark.
• Experience designing and developing ETL/ELT data pipelines.

Responsabilidades

• Design and maintain scalable data pipelines using Databricks.
• Develop and optimize ETL/ELT processes for analytics.
• Collaborate with teams to understand data requirements.

Conocimientos

Python

SQL

Data Modeling

Data Lakes

ETL/ELT

Apache Spark

Azure Databricks

Problem-solving

Version Control (Git)

English B2

Educación

Bachelor's Degree in Computer Science, Engineering, Information Systems, Mathematics or related field

Herramientas

Databricks

Azure Data Factory

Azure Synapse Analytics

Airflow

Kafka

Descripción del empleo

Data Engineer - Databricks

Zurich Capability Center is currently hiring a 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.

Required Skills and Experience

• 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.

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.
• 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.

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.

Location

Position available only for candidates located in Mexico City, State of Mexico, or Guadalajara.

Equal Opportunity

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.