• 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

• Design, develop, and maintain microservices, APIs, and system integrations. • Contribute to frontend and backend features as part of fullstack development. • Support ongoing development requests from our ticketing system and publisher integrations. • Build and maintain internal dashboards, reports, and data visualizations to support business teams. • Collaborate with other engineers to ensure code quality, scalability, and efficiency.