Staff Software Engineer- Eng

Software Engineering and Delivery Design, develop, test, and own scalable Java services, APIs, integrations, and distributed applications from technical design through deployment, observability, production support, and continuous improvement. Write clean, maintainable, modular, secure, and production-ready code. Translate business and technical requirements into practical designs, implementation plans, and actionable engineering tasks. Participate in sprint planning, backlog refinement, technical discussions, code reviews, testing, and release activities. Apply object-oriented design, design patterns, API design, data modeling, and clean coding practices. Identify technical risks, dependencies, and blockers early and drive them to resolution. Lead the technical implementation of complex features and cross-team initiatives by driving technical discussions, evaluating solution options, and guiding teams toward scalable, maintainable, and reliable designs. Review technical designs, code, database changes, automation workflows, and deployment approaches. Mentor engineers and promote consistent engineering, testing, troubleshooting, and documentation practices. Partner with architects, product owners, QA, SRE, security, and operations teams to deliver project outcomes. Help unblock engineers by resolving technical issues and clarifying implementation approaches. Distributed Systems, Integration, Automation, and Cloud Operations Design and support event-driven applications using Kafka topics, producers, consumers, event handlers, asynchronous processing, schema validation, idempotency, retries, timeouts, failure handling, and dead-letter processing. Develop GitHub Actions workflows, reusable workflows, custom actions, and parameterized jobs for build, test, deployment, and operational automation. Create automation scripts using PowerShell, Python, Bash, or similar technologies for application, infrastructure, database, and environment operations. Design and support MongoDB data-access components, including collections, indexes, queries, transactions, and performance-aware access patterns. Work with SQL Server and other relational databases for data processing, validation, migrations, troubleshooting, query optimization, and operational support. Deploy and support applications in GCP and other cloud environments, including configuration, service connectivity, secrets management, deployment automation, and runtime operations. Implement observability through structured logging, metrics, tracing, dashboards, alerts, and diagnostic tooling across applications, pipelines, databases, and infrastructure. Troubleshoot complex issues across application code, Kafka, GitHub Actions, scripts, databases, cloud infrastructure, networking, and deployment environments. Performance, Quality, Security, and Reliability Design and optimize services, APIs, event processing, database interactions, and automation for performance, scalability, and resource efficiency. Develop appropriate unit, integration, contract, workflow, and end-to-end tests for new and modified functionality. Apply secure engineering practices covering authentication, authorization, input validation, secrets, data protection, and least-privilege access. Participate in production readiness reviews, incident response, root-cause analysis, defect resolution, and post-release stabilization. Ensure changes are documented, testable, observable, supportable, and ready for production deployment. Cross-Project and Migration Support Contribute to multiple engineering projects based on organizational priorities and technical requirements. Develop migration utilities, validation tools, integration components, and operational automation when required. Collaborate with product, platform, infrastructure, migration, and engineering teams to resolve dependencies and technical issues. Design repeatable, observable, secure, and supportable solutions for migration and platform initiatives. AI-Assisted Engineering Use AI-assisted development tools responsibly to improve coding, testing, documentation, troubleshooting, and engineering productivity. Identify practical opportunities to use developer agents and automation tools to improve delivery speed and software quality. Validate AI-generated code, designs, test cases, and documentation before using them in engineering work. Follow security, privacy, intellectual property, and governance requirements when using AI-enabled tools. Experience building enterprise SaaS products, cloud-native applications, or large-scale platform services. Strong experience with Java backend development, REST APIs, microservices, distributed systems, and event-driven architecture. Hands-on experience with Kafka, asynchronous processing, message delivery guarantees, and event-schema management. Experience with MongoDB, SQL Server, database performance tuning, data validation, and migration activities. Experience with GitHub Actions, reusable workflows, custom actions, CI/CD automation, or infrastructure automation. Strong PowerShell, Python, Bash, or comparable scripting experience. Experience with GCP, Kubernetes, containers, cloud networking, service discovery, and secrets management. Experience with observability tools such as Grafana, Prometheus, OpenTelemetry, Splunk, Kibana, Datadog, or similar platforms. Experience with production support, incident management, root-cause analysis, and operational readiness. Experience mentoring engineers and leading technical implementation within an Agile or Scrum team. Experience using AI coding assistants, developer agents, or automation tools in the software development lifecycle. Key Attributes Strong hands-on developer who writes production code and automation regularly. Technical owner who can lead complex work across applications, integrations, databases, cloud platforms, and infrastructure. Practical problem solver who uses logs, metrics, traces, event data, workflow results, and database state to investigate issues. Comfortable working across Java, Kafka, GitHub Actions, GCP, MongoDB, SQL Server, and scripting. Quality-focused engineer who considers testing, security, performance, reliability, observability, and supportability. Effective collaborator across product, QA, architecture, SRE, operations, and peer engineering teams. Fast learner who can contribute across multiple projects and evolving technology areas. Clear communicator who can explain technical decisions and align stakeholders. Accountable engineer who takes ownership of delivery, operational outcomes, and continuous improvement.