Lead Data Engineer in Insurance
Posted 5
views
Summary
Lead Data Engineer serving a Fortune 100 insurance client via Iris Software — designs and maintains scalable ETL/ELT pipelines, dbt models, and stored procedures on cloud platforms like Snowflake, validates data quality, and collaborates with data architects and business analysts. Core stack: SQL, Python, Snowflake, dbt.
Step into a pivotal role as a Lead Data Engineer with Iris Software, focusing on the insurance sector. Leverage your SQL and Python skills for efficient data processing and analytics.
Iris’s Fortune 100 client seeks a Lead Data Engineer with 5-8 years of expertise in data engineering, primarily within the insurance domain. Candidates will design scalable ETL/ELT pipelines and optimize cloud-based platforms like Snowflake. Your role will directly impact data integration and analytics initiatives, enhancing business operations.
Key Responsibilities: • Design and maintain scalable ETL/ELT pipelines • Develop optimized Stored Procedures and dbt models • Utilize cloud platforms like Snowflake for data processing • Collaborate with Data Architects and Business Analysts • Perform data quality validation and troubleshooting
Requirements: • 5-8 years of Data Engineering experience • Strong expertise in SQL and Python • Knowledge of insurance data and business processes • Hands-on experience with workflow orchestration tools • Excellent communication skills for cross-functional collaboration
Drive impactful data solutions with Iris Software and make a difference in the insurance industry.
Iris’s Fortune 100 client seeks a Lead Data Engineer with 5-8 years of expertise in data engineering, primarily within the insurance domain. Candidates will design scalable ETL/ELT pipelines and optimize cloud-based platforms like Snowflake. Your role will directly impact data integration and analytics initiatives, enhancing business operations.
Key Responsibilities: • Design and maintain scalable ETL/ELT pipelines • Develop optimized Stored Procedures and dbt models • Utilize cloud platforms like Snowflake for data processing • Collaborate with Data Architects and Business Analysts • Perform data quality validation and troubleshooting
Requirements: • 5-8 years of Data Engineering experience • Strong expertise in SQL and Python • Knowledge of insurance data and business processes • Hands-on experience with workflow orchestration tools • Excellent communication skills for cross-functional collaboration
Drive impactful data solutions with Iris Software and make a difference in the insurance industry.