Guidepoint s Engineering team thrives on problem-solving and creating happier users. As Guidepoint aims to make individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new products to optimize the seamless delivery of our services.
As a Senior Software Engineer (Python, Microservices, Azure), you will take an active ownership role in architecting, implementing, and managing Guidepoint s growing Azure presence. The purpose of the role is to focus on delivering available, scalable enterprise PaaS-based solutions.
What You Will Do:
Develop and support scalable web/API/Microservices using Python and Azure Platform Services.
Build new applications/services/platforms and optimize existing solutions.
Refactor legacy components using modern, scalable platforms.
Design, implement, and deploy microservices on AKS using Docker, Kubernetes, Helm, and Azure DevOps YAML pipelines.
Perform end-to-end deployment, including infrastructure setup, configuration, and monitoring.
Collaborate with cross-functional teams (Full-stack, QA, DevOps, and Product teams) in agile SDLC processes.
Decompose portions of legacy applications into modern microservices architecture.
Write and maintain Unit Tests, Integration Tests, and implement robust CI/CD pipelines.
Design and manage JSON payloads and payload contexts.
Engage in database schema design and management, including updating tables and rows for large datasets.
Required Technical Qualifications:
8+ years of experience developing software using Python and Azure platform services.
Strong knowledge and hands-on experience in Microservices architecture, Docker, Kubernetes, and AKS.
Experience with CI/CD pipelines using Azure DevOps, including YAML files and Helm charts.
Proficiency in implementing unit testing, integration testing, and end-to-end testing.
Solid understanding of object-oriented programming, service-oriented architecture, and design patterns.
Experience in designing fault-tolerant, scalable, and resilient cloud solutions using the Well-Architected Framework.
Preferred Qualifications:
Experience in Data Engineering with Azure Databricks and PySpark.
Familiarity with data ingestion, processing, and analysis using distributed data processing frameworks.
Knowledge of designing and deploying solutions leveraging Azure services such as Azure SQL, Cosmos DB, Service Bus, Event Hub, and Key Vault.
Proficiency with Git concepts like branching, merging, pull requests, and conflict resolution utilizing Bitbucket or GitHub.
Hands-on experience with monitoring tools and logging frameworks in distributed systems.
Willingness to learn and apply cloud-native fault-tolerant architectures, including load balancing, clustering, and reducing/eliminating single points of failure.
Knowledge of Terraform, PowerShell scripting, and crafting architecture diagrams using tools like Lucidchart.
What We Offer:
Competitive compensation
Employee medical coverage
Central office location
Entrepreneurial environment, autonomy, and fast decisions
Casual work environment
About Guidepoint:
Guidepoint is a leading research enablement platform designed to advance understanding and empower our clients decision-making process. Powered by innovative technology, real-time data, and hard-to-source expertise, we help our clients to turn answers into action.
Backed by a network of nearly 1.5 million experts and Guidepoint s 1,300 employees worldwide, we inform leading organizations research by delivering on-demand intelligence and research on request. With Guidepoint, companies and investors can better navigate the abundance of information available today, making it both more useful and more powerful.
At Guidepoint, our success relies on the diversity of our employees, advisors, and client base, which allows us to create connections that offer a wealth of perspectives. We are committed to upholding policies that contribute to an equitable and welcoming environment for our community, regardless of background, identity, or experience.