Senior Data Engineer

Job Summary

Responsibilities At Principal, we don't just offer jobs; we offer careers that propel you forward. As a Senior Data Engineer, you will be at the forefront of crafting and implementing world-class data solutions that drive our actuarial and enterprise data initiatives. This role provides the outstanding opportunity to work with modern technologies and contribute to pioneering projects that have a tangible impact on our business and clients.

Responsibilities

• Collaborate with actuaries to gather, analyze, and translate actuarial requirements into technical solutions.
• Understand and support actuarial integration tools and related SaaS platforms.
• Compose, build, and maintain scalable data lakes on AWS to support actuarial and enterprise data initiatives.
• Create and maintain CI/CD pipelines using GitHub Actions, Docker, AWS CDK, and AWS SAM.
• Participate in architecture discussions and contribute to crafting new cloud-native solutions while migrating existing data applications to AWS.
• Develop and optimize AWS Glue ETL jobs using PySpark, Boto3, and AWS CDK.
• Build, implement, and maintain ETL frameworks and data processing solutions following established guidelines.
• Develop, test, and deploy ETL scripts using PyTest and containerized environments.
• Improve database performance through query optimization, indexing strategies, partitioning, and data modeling techniques.
• Transition current AWS CloudFormation (CFN) infrastructure to AWS CDK and develop reusable infrastructure-as-code frameworks.

Qualifications

Must-Have Skills

• Hands-on experience with actuarial integrate tools (Milliman) and actuarial SaaS platforms.
• Strong understanding of actuarial concepts, terminology, calculations, and modeling processes.
• 4 to 7 years of hands-on experience in AWS Data Engineering, ETL development, and cloud-based data platform implementations.
• Extensive experience with AWS cloud services, including: AWS Glue, Athena, Lambda, S3, CloudFormation (CFN), AWS CDK, SNS, IAM, RDS, DynamoDB, CloudWatch, Boto3.
• Proficiency in Python and PySpark for large-scale data processing and ETL development.
• Experience developing and managing CI/CD pipelines with GitHub Actions and Docker.
• Practical experience in applying Infrastructure as Code (IaC) through AWS CDK and CloudFormation.
• Strong knowledge of data lake architecture, ETL frameworks, and cloud-based data engineering practices.
• Experience with application deployment using AWS SAM.

Good-to-Have Skills

• Experience working on data-intensive and large-scale analytics projects.
• Knowledge of insurance, actuarial, or financial services domains.
• Familiarity with data governance, data quality, and data security guidelines.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.