Job Description

About Chubb

Chubb is a world leader in insurance. 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. The company is 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 employs approximately 40,000 people worldwide. Additional information can be found at: www.chubb.com .

About Chubb India

At Chubb India, we are on an exciting journey of digital transformation driven by a commitment to engineering excellence and analytics. With a team of over 2500 talented professionals, we foster a startup mindset that promotes collaboration, diverse perspectives, and a solution-driven attitude. We are dedicated to building expertise in engineering, analytics, and automation, empowering our teams to excel in a dynamic digital landscape.


We offer an environment where you will be part of an organization that is dedicated to solving real-world challenges in the insurance industry. Together, we will work to shape the future through innovation and continuous learning.

Position Details:

Job Title

: Data Engineer

Function/Department

: Technology

Location

: Hyderabad/Bengaluru - Hybrid

Employment Type

: Full-time

Job Summary:

As a Data Engineer, you will be responsible for designing, developing, and maintaining data integration solutions using SQL, Databricks, Python, and Snowflake. You will work closely with data analysts, data scientists, and other stakeholders to ensure data availability, quality, and performance.

Key Responsibilities:

Design and implement data pipelines using Databricks and Python to integrate data from various sources into Snowflake. Develop and optimize data models in Snowflake to support analytical workloads and reporting needs. Write complex SQL queries for data manipulation, transformation, and analysis within Snowflake. Utilize Databricks for data processing and transformation tasks, ensuring efficient data workflows. Monitor and optimize the performance of data pipelines and Snowflake queries to ensure efficient data processing. Collaborate with cross-functional teams to understand data requirements and deliver high-quality data solutions. Implement data governance practices, including data quality checks, data lineage, and compliance measures. Troubleshoot and resolve data-related issues, ensuring data integrity and reliability. * Stay updated with the latest trends and best practices in data engineering, Databricks, Python, and Snowflake.