Chubb's PRS Data Science team builds data pipelines and analytical solutions that power predictive models directly supporting our insurance products and business partners. We operate in a fast-paced, collaborative environment where engineers own work end-to-end—from ingestion and transformation to delivery of production-ready datasets consumed by data scientists and decision-makers across the organization.
We are looking for an early to mid-career Data Engineer who is passionate about building reliable, scalable pipelines and who thrives at the intersection of engineering and business impact.
Responsibilities
Design, build, and maintain production ETL pipelines for predictive modeling workloads.
Develop and optimize PySpark jobs on Databricks, ensuring 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 in a clear, concise manner.
Partner with platform and cloud engineering teams on Azure infrastructure and Databricks workspace management.
Technical Skills
Python: Expert-level proficiency; strong command of data engineering libraries (pandas, PySpark, SQLAlchemy), code quality practices, and packaging.
SQL: Expert-level; able to write complex analytical queries, window functions, CTEs, and performance-tune queries across multiple platforms.
Apache Spark / PySpark: Comfortable developing and debugging distributed data processing jobs; understands Spark execution model and optimization basics.
Databricks: Hands-on experience with notebooks, Delta Lake, Jobs/Workflows, and cluster configuration.
Azure: Working experience with core Azure data services (Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics, or equivalent).
SQL Server & Synapse Analytics: Experience querying and loading data; understanding of schema design and indexing strategies.
Snowflake: Practical experience with Snowflake warehousing, data loading patterns, and role-based access.
Windows: Comfortable working in a Windows-based development environment.
Education & Experience
Bachelor's degree in Computer Science, Information Systems, Mathematics, Engineering, or a related quantitative field.
2-4 years of professional experience in a data engineering, analytics engineering, or software engineering role with a significant data focus.
Soft Skills
Strong written and verbal communication skills; able to present technical concepts to non-technical business audiences.
Collaborative team player who engages proactively with data scientists, analysts, and business partners.
Detail-oriented with a bias toward clean, maintainable, and well-tested code.
Comfortable managing multiple priorities in a fast-paced delivery environment.
Nice To Have
CLI tools: Familiarity with shell scripting, command-line data tools, and working in Linux environments.
Version control: Experience with Git-based workflows in a team setting.
Orchestration: Exposure to workflow orchestration tools (e.g., Apache Airflow, Azure Data Factory pipelines, Databricks Workflows).
Insurance / financial services domain: Prior experience in a regulated industry is a plus but not required.
CI/CD: Familiarity with automated testing and deployment pipelines for data assets.
The pay range for the role is $82,000 to $92,000. The specific offer will depend on an applicant’s skills and other factors. This role may also be eligible to participate in a discretionary annual incentive program. Chubb offers a comprehensive benefits package, more details on which can be found on our careers website. The disclosed pay range estimate may be adjusted for the applicable geographic differential for the location in which the position is filled.
About UsSkills Required
- Bachelor’s degree in Computer Science, Information Systems, Mathematics, Engineering, or a related quantitative field
- 2–4 years of professional experience in data engineering, analytics engineering, or software engineering with significant data focus
- Expert-level proficiency in Python, including pandas, PySpark, SQLAlchemy, code quality practices, and packaging
- Expert-level SQL skills, including complex analytical queries, window functions, CTEs, and query performance tuning
- Experience developing and debugging Apache Spark and PySpark distributed processing jobs
- Hands-on Databricks experience with notebooks, Delta Lake, Jobs/Workflows, and cluster configuration
- Working experience with Azure data services such as Azure Data Factory, Azure Data Lake Storage, or Azure Synapse Analytics
- Experience with SQL Server and Synapse Analytics, including querying, loading data, 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
- Strong written and verbal communication skills, including presenting technical concepts to non-technical audiences
- Collaborative, proactive approach with data scientists, analysts, and business partners
- Detail-oriented approach to clean, maintainable, and well-tested code
- Ability to manage multiple priorities in a fast-paced delivery environment
- Familiarity with shell scripting, command-line data tools, and 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, financial services, or another regulated industry
- Familiarity with automated testing and CI/CD deployment pipelines for data assets
Chubb Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Chubb and has not been reviewed or approved by Chubb.
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Healthcare Strength — Healthcare coverage includes multiple medical plan options with preventive care, plus dental and vision, alongside HSAs/FSAs, telemedicine, and wellness resources. The breadth of offerings is presented as comprehensive for a large insurance employer.
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Retirement Support — A 401(k) plan with company contributions anchors the financial benefits, complemented by life and disability insurance. These programs reinforce long-term savings and protection.
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Strong & Reliable Incentives — Performance-based and year-end bonuses are part of the total rewards, with structured reviews supporting incentive opportunities. These components provide compensation beyond base salary.
Chubb Insights
What We Do
Chubb is the world’s largest publicly traded property and casualty insurance company. With operations in 54 countries and territories, Chubb provides commercial and personal property and casualty insurance, personal accident and supplemental health insurance, reinsurance and life insurance to a diverse group of clients. As an underwriting company, we assess, assume and manage risk with insight and discipline. We service and pay our claims fairly and promptly. The company is also defined by its extensive product and service offerings, broad distribution capabilities, exceptional financial strength and local operations globally. Parent company Chubb Limited is listed on the New York Stock Exchange (NYSE: CB) and is a component of the S&P 500 index. Chubb maintains executive offices in Zurich, New York, London, Paris and other locations, and employs 31,000 people worldwide. Additional information can be found at: chubb.com.
