Principal Software Engineer

This is a key role for one of Weekday's clients seeking an experienced Principal Software Engineer to lead initiatives in Risk Analytics, Digital Experience Monitoring (DEM), and Data Engineering.

The ideal candidate will have a strong foundation in data analytics, system observability, risk management solutions, and backend engineering with deep expertise in Golang, Java, AWS cloud services (Kinesis, Redshift, Elasticsearch) and exposure to DEM tools.

Key Responsibilities:
Lead the design and development of Risk Analytics and DEM solutions to monitor system performance, user experience, and operational risks.
Architect and optimize scalable data pipelines and analytics applications leveraging AWS services (Kafka, Redshift, Elasticsearch, S3, Lambda).
Develop real-time and batch processing applications using Golang and Java to support risk assessment and predictive analytics.
Implement observability and monitoring frameworks to enhance system resilience and reliability.
Collaborate with cross-functional teams, including data scientists, risk analysts, and engineering teams, to develop data-driven decision-making frameworks.
Ensure data security, compliance, and governance across all analytics platforms.
Optimize data ingestion, storage, and retrieval mechanisms for high availability and low-latency insights.
Mentor and guide engineering teams, promoting best practices and technical excellence.
Stay ahead of industry trends, including AI/ML-driven monitoring and cloud-native solutions, to enhance system performance and security.
Required Qualifications:
12+ years of experience in software development, data analytics, risk intelligence, and monitoring solutions.
Expertise in Golang and Java for backend development and data processing.
Strong hands-on experience with AWS cloud services (Kafka, Redshift, Elasticsearch, Glue, S3, Lambda).
Experience with Digital Experience Monitoring (DEM) tools.
Knowledge of big data processing frameworks (Spark, Flink).
Proven experience in risk analytics, compliance monitoring, or fraud detection.
Strong understanding of observability solutions, Application Performance Monitoring, and log monitoring.
Experience with real-time streaming architectures (Kafka, AWS Kinesis).
Proficiency in SQL, NoSQL databases, and data modeling.
Strong problem-solving and communication skills.
Preferred Qualifications:
Experience with AI/ML for predictive risk analytics.
Expertise in containerized and serverless architectures (Docker, Kubernetes, AWS Lambda).
Familiarity with CI/CD automation, DevOps, and Infrastructure as Code (IaC).
Exposure to cybersecurity risk assessment and compliance frameworks.