Software Engineer

We are seeking an experienced Software Engineer, Data Pipelines to join a team supporting critical Fraud and Claims Analytics initiatives. In this role, you will design, develop, and optimize large-scale data pipelines that process and transform enterprise data assets while supporting the organization’s migration from Teradata to Google Cloud Platform (Google Cloud Platform)., You will work closely with business stakeholders, data engineers, and platform teams to build scalable, reliable solutions that enable fraud detection, claims analysis, and data-driven decision making across the enterprise. What You’ll Do

• Design, develop, and maintain scalable ETL and data pipeline solutions.
• Support the migration of large-scale data platforms from Teradata to Google Cloud Platform.
• Build and optimize data processing workflows using PySpark, Python, SQL, and Ab Initio.
• Develop and support data ingestion, transformation, and orchestration processes.
• Collaborate with stakeholders within Fraud and Claims Analytics to gather requirements and deliver data solutions.
• Ensure data quality, reliability, performance, and operational excellence across data platforms.
• Monitor, troubleshoot, and optimize production data pipelines.
• Contribute to cloud-based architecture and platform modernization initiatives., The team supports a large-scale data ecosystem consisting of:
• Google Cloud Platform (Google Cloud Platform)
• BigQuery
• PySpark
• Python
• Hadoop
• Ab Initio
• Dremio
• S3 Storage Grid
• Teradata (legacy platform)

The environment currently manages approximately 1,000 TB of data across 600-700 tables and is undergoing a strategic migration to Google Cloud Platform. Additional Information

• Backfill position.
• Charlotte, NC is the preferred location.
• Standard business hours with occasional after-hours support for critical production issues.
• Hybrid attendance is mandatory with three in-office days per week.

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or equivalent practical experience.
• 5+ years of software engineering or data engineering experience.
• 4-6 years of hands-on experience with:
• SQL
• ETL development
• Python and PySpark
• Autosys
• Ab Initio
• Cloud technologies
• Experience building and supporting large-scale data pipelines and distributed data processing systems.
• Experience working in enterprise data environments with complex datasets.

Preferred Qualifications

• Experience with Google Cloud Platform (Google Cloud Platform), including BigQuery.
• Experience with Kafka, Hadoop, and Teradata.
• Familiarity with Dremio and large-scale storage solutions.
• Google Cloud certifications.
• Experience supporting data modernization and cloud migration initiatives.
• Strong problem-solving, communication, and stakeholder management skills., A senior-level data engineer with deep expertise in building enterprise-scale data pipelines, strong experience with PySpark and ETL frameworks, and a proven track record of delivering cloud-based data solutions, preferably within Google Cloud Platform.