Streaming Data

About the Opportunity As a Senior Engineer, you will shape the technical direction, reliability, and scalability of enterprise analytics platforms that support mission-critical exam operations. You will lead the design of resilient data architectures, real-time telemetry pipelines, and high-performance reporting systems that must perform flawlessly during peak exam delivery. You bring strong cloud full-stack engineering experience, with deep knowledge across backend services, data platforms, APIs, and front-end analytics applications. You are comfortable designing and operating cloud-native solutions end to end-from data ingestion and transformation to secure service layers and intuitive dashboard experiences. You will drive engineering excellence by establishing sound architectural patterns, automation standards, and observability practices that reduce risk and improve operational readiness. This role requires expertise in scalable cloud infrastructure, performance optimization, data integrity, secure system design, and platform reliability.

In this role, you will:

• Develop and maintain a thorough understanding of the customer's business processes and operations
• Work closely with Solutions Architect and other Lead Engineers evaluating feature requests, providing level-of-effort estimates and contributing to sprint planning
• Conduct and participate in peer code and design reviews
• Shape the technical direction, scalability, and reliability of enterprise analytics platforms supporting mission-critical exam operations
• Design, implement, and maintain resilient cloud-native data architectures, real-time telemetry pipelines, APIs, and high-performance reporting systems
• Build secure, scalable full-stack solutions spanning backend services, data platforms, and front-end analytics applications
• Lead end-to-end solution design-from data ingestion and transformation to secure service layers and intuitive dashboard experiences
• Establish and enforce strong architectural patterns, automation standards, and observability practices
• Engineer and maintain systems with a focus on continued scalability, data integrity, high availability, and long-term reliability
• Embed monitoring, telemetry, and operational readiness into all platform components
• Serve as a technical anchor for the team, guiding complex design decisions and large-scale problem-solving efforts
• Mentor engineers and elevate development standards across cloud, data, and full-stack domains
• Clearly communicate architectural tradeoffs, technical strategy, and platform decisions to cross-functional stakeholders
• Promote best practices in secure system design, automation, performance optimization, and resilient engineering
• Partner with product, operations, and security stakeholders to align technical solutions with business and operational priorities
• Support high-stakes exam readiness through proactive risk identification, capacity planning, and reliability reviews
• Foster a culture of ownership, documentation, accountability, and continuous improvement

• 7+ years of experience designing, building, and operating scalable, cloud-native applications, data pipelines, and analytics platforms in high-availability environments
• 3+ years of experience developing modern front-end applications using TypeScript and React, with a strong focus on analytics dashboards and data-driven interfaces
• Strong hands-on experience with backend technologies such as Node.js (preferably with TypeScript) and Python, building APIs, event-driven services, and data processing components that power real-time and near real-time analytics
• Experience designing and maintaining reliable, scalable data ingestion, transformation, and orchestration pipelines to support operational and analytical workloads
• Expertise in developing responsive, secure, and high-performance user interfaces using TypeScript, JavaScript, HTML, and CSS
• Experience implementing role-based access control (RBAC) and secure access patterns to ensure proper data governance and protection of sensitive information
• Experience with asynchronous programming, event-driven architectures, and telemetry/event-streaming patterns
• Hands-on experience with real-time data monitoring and analytics platforms such as Grafana and InfluxDB
• Strong experience with cloud-based data stores and query engines such as Amazon Redshift, Athena, DynamoDB, and S3-based data lakes, including performance optimization and trend analysis.
• Deep expertise in data modeling and transformation within AWS, leveraging services such as Glue, Redshift, Athena, EMR, Lambda, and S3 to build scalable, performant, and reliable analytical data foundations
• Experience implementing Machine Learning (ML) and Artificial Intelligence (AI) solutions within analytics platforms, including integrating predictive models, anomaly detection, trend analysis, or intelligent insights into production systems
• Familiarity with ML lifecycle practices, model deployment, monitoring, and operationalization using platforms such as SageMaker Studio, Amazon Quick Suite or similar environments
• Deep knowledge of AWS services including Lambda, SNS, SQS, S3, Step Functions, IAM, KMS, and CloudWatch
• Experience provisioning and managing cloud infrastructure using Infrastructure as Code tools such as AWS CDK, CloudFormation, Terraform, and AWS CLI
• A strong focus on scalability, data integrity, reliability, and operational readiness