This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role offers the opportunity to design, build, and automate cutting-edge cloud solutions in a dynamic, fast-paced technology environment. You will be responsible for full stack development, Azure infrastructure management, CI/CD pipeline automation, security remediation, and containerized application deployment. Collaborating across cross-functional teams, you will help implement modern DevOps practices and support analytics and AI-driven workflows. The ideal candidate thrives in an agile environment and enjoys solving complex infrastructure and application challenges end-to-end. - Build, manage, and maintain Azure cloud infrastructure and associated services. - Develop and automate CI/CD pipelines using Azure DevOps and Git. - Implement Infrastructure as Code (IaC) with Terraform and automate platform tasks. - Deploy and manage containerized applications with Docker, Kubernetes, and Helm. - Resolve security violations and apply cybersecurity best practices across the platform. - Support analytics and data engineering initiatives using Azure Databricks and AI tools. - Write automation scripts for UNIX/Linux environments and collaborate with cross-functional teams to deliver integrated cloud solutions. - Participate in SAFe Agile processes, contributing to sprint planning, development, and delivery. Qualifications - 6+ years of hands-on experience in Azure cloud engineering and full stack development. - Strong experience with Terraform, CI/CD, Git, and DevOps practices. - Proficient in Java and Python, including development, debugging, and testing frameworks such as JUnit. - Knowledge of containerization technologies, including Docker, Kubernetes, and Helm. - Experience implementing security best practices and managing enterprise-grade cloud infrastructure. - Familiarity with data engineering, analytics workflows, and AI/ML tooling within Azure. - Strong problem-solving, communication, and collaboration skills in cross-functional and Agile environments. Benefits - Competitive salary and performance-based incentives. - Comprehensive medical, dental, and vision coverage. - Flexible work arrangements with remote-friendly options. - Professional development budget and continuous learning opportunities. - Paid vacation, sick leave, and holidays. - Access to modern development tools, cloud platforms, and collaboration technologies. - Employee recognition programs and supportive team culture.

• Architect and Implement Systems: Build robust systems end to end and manage interactions with various data stores and 3rd party APIs • Own the Integration Lifecycle: Lead the design and implementation of new carrier integrations while incorporating them into our new product offering • Drive Data Reliability: Support reliable databases and APIs designed for real-time automated decision-making • Scale with Modern Tooling: Deploy and manage software using industry-standard tooling like Kubernetes clusters and Argo CD • Collaborate for Impact: Work in an agile environment, interviewing users to understand needs and coordinating with Product, Design, and Business teams to ship impactful features

• Build and Scale Observability-as-Code • Design and maintain Python tooling and Terraform modules that standardize Datadog configuration across services. • Eliminate manual setup by codifying monitors, dashboards, SLOs, and alerting patterns. • Improve consistency, repeatability, and reliability of observability across the organization. • Establish Reliable & Standardised Instrumentation • Define and implement observability blueprints that integrate high‑fidelity metrics, logs, and traces into the development lifecycle. • Codify best practices so teams get out-of-the-box visibility without needing deep observability expertise. • Raise the baseline for service health, debuggability, and operational readiness • Optimize Datadog Usage and Cost • Own critical parts of the Datadog platform configuration. • Improve data quality, signal-to-noise ratio, and alert reliability. • Partner with teams to adopt telemetry effectively while managing ingestion and alerting costs. • Maintain and Evolve Platform Components • Upgrade and maintain tracers, agents, and shared observability libraries. • Ensure upgrades are automated, backwards-compatible, and minimally disruptive to product teams. • Reduce operational risk by improving rollout and validation processes. • Integrate Observability Across Infrastructure • Collaborate with Platform and Infrastructure teams to embed monitoring into systems such as Kafka, gRPC services, Kubernetes, and AWS-managed services. • Improve production visibility and reduce mean time to detect (MTTD) and resolve (MTTR) incidents • Deliver High-Quality, Production-Ready Code • Write clean, well-tested, and maintainable Python code and Terraform modules. • Participate in architecture and design reviews; provide thoughtful feedback in code reviews. • Take ownership of projects end-to-end, from design and implementation through production rollout and support. • Mentorship & Collaboration • Assist team members to solve problems and develop their own skills. • Foster a collaborative mindset within the team.

• Build and operate data services driving our applications and APIs • Collaborate with team members and across Engineering to iteratively prototype and develop new functionality • Partner with product managers and other Zusers