- Design and architect scalable data pipelines using AWS Glue, Eventbridge, DynamoDB to process life insurance data including policy records, claims, actuarial datasets.
- Write and optimize ETL and reconciliation workflows using PySpark and Python to transform raw policyholder data into analytics-ready datasets for reporting and decision-making.
- Build and implement event-driven data solutions on AWS, levaraging SQS, SNS, and API integrations to enable real-time processing of insurance transactions and policy events
- Implement snowflake data masking and row level security policies to ensure snesitive policyholder and beneficiary data is protected.
- Write and optimize DAX queries and PowerBI dataflows to connect directly to AWS Redshift and S3 data sources, ensuring actuarial, finance, and business teams have access to reliable and up-to-date life insurance dashboards for mortality analysis, and lapse reporting
- Build python script in Dataiku code environment to develop data processing logic that meets life insurance business and regulatory requirements
- Write and optimize ETL workflows using PySpark and Python to transform raw policyholder data into analytics-ready datasets for reporting and decision-making.
- Write SQL queries and stored procedures in Amazon redshift to support life insurance reporting, premium reconciliation, and claim analytics
- Develop end-to-end data workflows in Dataiku, integrating life insurance data sources such as policy administration systems, claims databases and actuarial feeds
- Write and optimize Delta Lake table implementations in Databricks to support efficient storage, ACID transactions, and time travel queries on life insurance datasets.
- Build and maintain alteryx server scheduled workflows to automate end-to-end data processing pipelines for life insurance and claims reporting on Tableau.
- Work on Jira tickets for the sprint plan and utilize Gitlab repositories and confluence and participate in retrospective meetings
Minimum Education Requirement:- This position requires, at a minimum, a bachelor’s degree in computer science, computer information systems, information technology, relevant engineering, (computer engineering, software engineering, electronic engineering or related) or a combination of education and experience equating to the U.S. equivalent of a Bachelor’s degree in one of the aforementioned subjects.
