Join Optum, a global leader dedicated to improving health outcomes through innovative technology. You'll be part of a team developing a cutting-edge log processing pipeline, processing vast amounts of cloud data daily. This role offers a unique opportunity to influence the future of health optimization on a global scale within an inclusive culture that values collaboration and career growth.

This is a hands-on role focused on building a new, high-scale data pipeline. You will architect and implement solutions that transform log data from AWS, GCP, and Azure into a format optimized for Splunk Cloud. The goal is to create efficient, observable, and cost-effective data processing for enhanced security detection capabilities.

Design and develop a scalable, serverless event processing pipeline using AWS Lambda, integrating with Kinesis Data Streams for real-time data ingestion.

Implement robust event parsing and transformation logic to handle diverse cloud log formats and map them to Splunk's Common Information Model (CIM).

Develop intelligent data routing strategies to optimize Splunk licensing costs by implementing tiered data retention.

Ensure high availability and performance through comprehensive monitoring, alerting, and error handling mechanisms, including dead-letter queues and retry logic.

Collaborate with cross-functional teams on stream integration, architecture decisions, code reviews, and CI/CD pipeline development.

Write infrastructure as code using Terraform to automate the deployment and management of all pipeline components.

Possess 5+ years of professional software engineering experience with a strong focus on building high-throughput streaming data pipelines.

Demonstrate deep expertise in cloud platforms, with a primary focus on AWS (Lambda, Kinesis, S3, IAM, CloudWatch) and working knowledge of GCP and Azure environments.

Proficiency in Go for developing production-grade Lambda functions and a solid understanding of Python for supporting services and automation.

Experience with infrastructure as code tools like Terraform and familiarity with CI/CD practices and Git-based workflows.

Strong understanding of event-driven architecture, data serialization formats, and observability principles for production systems.