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Chubb

Global property & casualty insurer

Data Engineer

Data EngineeringPosted on Nov 6
Full-timeIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Information Systems, Mathematics, Engineering, or a related quantitative field.
  • Two to four years of professional experience in a data engineering, analytics engineering, or software engineering role with a significant data focus.
  • Expert-level proficiency in Python, including data engineering libraries such as pandas, PySpark, and SQLAlchemy, code quality practices, and packaging.
  • Expert-level SQL skills, including complex analytical queries, window functions, common table expressions, and query performance tuning across multiple platforms.
  • Ability to develop and debug distributed Apache Spark/PySpark jobs and understand the Spark execution model and optimization basics.
  • Hands-on experience with Databricks notebooks, Delta Lake, Jobs/Workflows, and cluster configuration.
  • Working experience with core Azure data services such as Azure Data Factory, Azure Data Lake Storage, and Azure Synapse Analytics, or equivalent services.
  • Experience querying and loading data with SQL Server and Synapse Analytics, including understanding schema design and indexing strategies.
  • Practical experience with Snowflake warehousing, data-loading patterns, and role-based access.
  • Comfort working in a Windows-based development environment.
  • Ability to communicate technical concepts clearly to non-technical business audiences.
  • Ability to manage multiple priorities in a fast-paced delivery environment.

Responsibilities

  • Design, build, and maintain production ETL pipelines for predictive modeling workloads.
  • Develop and optimize PySpark jobs on Databricks to ensure performance and reliability at scale.
  • Write complex, well-structured SQL for data transformation, validation, and reporting across SQL Server, Synapse Analytics, and Snowflake.
  • Collaborate with data scientists to understand data requirements and translate them into robust engineering solutions.
  • Monitor pipeline health, troubleshoot failures, and implement improvements to data quality and observability.
  • Document data flows, schemas, and pipeline logic to maintain institutional knowledge.
  • Present project progress, architecture decisions, and results to business stakeholders clearly and concisely.
  • Partner with platform and cloud engineering teams on Azure infrastructure and Databricks workspace management.

Desired Qualifications

  • Familiarity with shell scripting, command-line data tools, and working in Linux environments.
  • Experience with Git-based workflows in a team setting.
  • Exposure to workflow orchestration tools such as Apache Airflow, Azure Data Factory pipelines, or Databricks Workflows.
  • Prior experience in insurance or financial services, or another regulated industry.
  • Familiarity with automated testing and deployment pipelines for data assets.

About the Company

Chubb

Global property & casualty insurer

Chubb is the world’s largest publicly traded property and casualty insurer, offering commercial and personal insurance, reinsurance, life and health products across 54 countries. It underwrites policies by evaluating risk, pricing premiums, and paying claims fairly and promptly when covered events occur. Its breadth of products, extensive distribution, and strong financial position distinguish it from competitors and enable it to serve diverse clients globally. Its goal is to help people and businesses manage risk with clear policy terms and reliable financial protection.

Company size
10,001+
Company stage
IPO
Headquarters
Zurich, Switzerland
Founded
1985

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