Data Engineer

JOB DESCRIPTION

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.

QUALIFICATIONS

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 communicat...