Resilient Co.

• Design and build scalable data pipelines to ingest, transform, and curate data from APIs, databases, files, and event streams. • Lead technical design reviews and translate complex business needs into enterprise-grade data solutions. • Develop and optimize advanced data models (dimensional, data vault, domain-driven, canonical) to support analytics, BI, and productized datasets. • Champion SDLC best practices, continuous delivery, and infrastructure automation using CI/CD and Infrastructure as Code. • Optimize complex distributed workloads using SQL, Python; mentor others on tuning and scalable design patterns. • Build reusable data frameworks, libraries, and reference architectures to accelerate team productivity and platform adoption. • Perform root-cause analysis for major data incidents, lead long-term remediation, and drive operational reliability improvements. • Provide technical mentorship, guide code reviews, and help shape engineering capability maturity. • Collaborate with Architects, Data Leads, Product Owners, and cross-functional engineering teams to define long-term data strategies. • Perform other duties as assigned.

• Design, develop, and maintain highly scalable backend services and enterprise applications using Python and Java. • Build high-performance solutions capable of processing and managing large-scale datasets. • Develop and maintain RESTful APIs and microservices integrations with internal and external systems. • Design software architectures that prioritize reliability, scalability, security, and operational efficiency. • Optimize application performance, troubleshoot production issues, and implement proactive monitoring. • Implement automated testing, CI/CD pipelines, and infrastructure management practices. • Deploy and operate containerized applications using Kubernetes, collaborating on orchestration and runtime configuration. • Participate in code reviews and promote engineering best practices, coding standards, and quality assurance processes. • Collaborate with architects, product owners, DevOps engineers, and business stakeholders to deliver platform features. • Support production environments to ensure system availability, resiliency, and performance. • Contribute to continuous improvement initiatives focused on platform modernization and operational excellence.

• Own and maintain a prioritized product backlog with epics, features, and user stories. • Write clear acceptance criteria and ensure development teams understand and accept user stories. • Drive agile ceremonies including sprint planning, backlog refinement, and sprint reviews. • Collaborate with UX designers and developers to ensure a seamless, user-centered digital experience. • Translate product manager vision and market insights into prioritized features and a delivery roadmap. • Act as the communication bridge between technology teams and product managers to resolve questions and align expectations. • Communicate product status, updates, and outcomes to stakeholders and relevant audiences. • Mentor Product Owners and contribute best practices across teams. • Identify opportunities for process or technology improvements within the team.

• Design and develop high-performing, scalable web applications using .NET and React. • Build and maintain backend services and data access using SQL and related technologies. • Implement cloud solutions and infrastructure patterns aligned with Microsoft Azure. • Apply Infrastructure as Code practices (Terraform / OpenTofu) to provision and manage resources. • Collaborate in agile ceremonies and contribute to sprint planning, estimation, and retrospectives. • Produce technical specifications, process flow diagrams, and clear documentation for technical and non-technical stakeholders. • Troubleshoot, enhance, and support existing applications based on user feedback and incidents. • Ensure solutions meet security, cloud, compliance, and quality standards. • Work with architects and cross-functional teams to translate requirements into maintainable software with long-term ownership in mind.

• Design and develop advanced ServiceNow configurations and customizations across CSM, ITSM, HRSD, and SLO modules. • Architect and implement integrations using IntegrationHub, MID Server, REST/SOAP APIs, and Workflow Data Fabric. • Build and maintain business rules, client scripts, script includes, UI actions, and scheduled jobs using server-side JavaScript and Glide APIs. • Lead technical design reviews and code reviews, enforcing Azure DevOps stage gates and SDLC standards. • Deliver Now Assist (GenAI) feature rollouts including AI-assisted case deflection and knowledge article generation. • Partner with platform administrators on upgrade readiness, patching cycles, and regression test planning. • Translate complex HRSD, IT Service Desk, and CSM requirements into scalable technical solutions with complete documentation. • Produce and maintain technical design documents, integration specifications, and operational runbooks. • Mentor mid-level developers and system administrators on platform best practices, performance tuning, and security hardening. • Ensure deployments follow Dev > Test > Prod update set pipelines and Azure DevOps release controls.

• Serve as the single technical lead and client-facing advisor across application, data, and reporting initiatives. • Assess Excel-heavy workflows, formulas, workbooks, and reporting bottlenecks to identify inefficiencies and instability. • Define migration paths from Excel-based processes to SQL, centralized reporting layers, and Power BI dashboards. • Evaluate data pipelines, ingestion processes, reporting limitations, and platform constraints and recommend architecture improvements. • Govern and lead one developer working on a live Django/JavaScript application running on Windows Server/IIS. • Migrate code from local storage into a hosted version control system and establish CI/CD practices to replace manual deployments. • Conduct comprehensive code reviews and recommend practical remediation for technical debt. • Implement structured application-level logging, monitoring dashboards, and alerting to replace basic server stat tracking. • Define and deliver SDLC governance, development standards, data retention practices, and developer onboarding documentation. • Deliver a practical roadmap with quick wins, execution priorities, and longer-term modernization opportunities. • Lead and coordinate nearshore or distributed resources, assign task-level work, and ensure delivery aligns with business priorities. • Act as an escalation point and technical translator for leadership, balancing hands-on delivery with advisory responsibilities. • Identify opportunities for automation, AI, and RPA to improve future-phase scalability.

• Design and configure Okta policies, access controls, and token settings for applications and APIs. • Integrate applications with Okta for authentication and authorization using established patterns. • Support migrations of Okta configurations and applications between environments. • Replace OAG dependencies by implementing OIDC and Apache-based access where appropriate. • Troubleshoot authentication, authorization, and access issues across integrated applications. • Collaborate directly with application and identity teams to gather requirements and implement solutions. • Document configuration changes, integration details, and operational runbooks. • Support Okta automation and AI initiatives when capacity permits to improve operational efficiency.

• Design, develop, and maintain scalable Python applications and services. • Build reusable, maintainable, and well-documented code components. • Develop backend services and APIs using Django and/or Flask. • Participate in architecture reviews and technical design discussions. • Troubleshoot and optimize production systems. • Develop and optimize large-scale data processing pipelines using PySpark. • Process, transform, and analyze large structured and unstructured datasets. • Build scalable ETL and data ingestion frameworks. • Optimize distributed data processing workloads for performance and reliability. • Implement data science algorithms and predictive models in production environments. • Collaborate with data scientists to operationalize machine learning solutions. • Develop and optimize ML pipelines using scikit-learn and related libraries. • Support model deployment, validation, and monitoring processes. • Perform complex data wrangling, cleansing, and transformation activities. • Build data pipelines utilizing Pandas, NumPy, PyArrow, and PySpark. • Develop solutions for handling large-scale datasets and analytical workloads. • Design and develop RESTful APIs supporting high-volume data operations. • Build secure, scalable services capable of handling significant throughput. • Design and optimize data access patterns across relational and NoSQL databases. • Work with efficient SQL queries and database integrations.

• Construcción, integración de despliegue de los pipelines de los productos de la empresa • Dominio de contenedores (Docker) y orquestadores (Kubernetes) • Participar en el desarrollo de nuevas infraestructuras de servicios. • Contribuir a la base de conocimiento del área. • Participar en la formulación de normas, estándares y políticas referentes al área. • Monitorear el funcionamiento de los recursos. • Identificar y mantenerse actualizada la información de novedades tecnológicas y de gestión. • Velar por la seguridad, dentro de su ámbito de acción e independientemente de su nivel de criticidad, de la información y los activos que deba gestionar según su rol. • Velar por el cumplimiento de procedimientos • Velar por la mejora continua del área

• Write and maintain UI microcopy including labels, tooltips, errors, and confirmations • Create emails, notifications, and other lifecycle communications • Draft task flows and onboarding steps that guide users through product experiences • Ship content quickly and iterate based on user feedback and product signals • Apply established content frameworks, guidelines, and patterns consistently • Identify and resolve gaps, inconsistencies, and edge cases in content • Partner closely with the AI Content Strategist, Product Designers, and Product Managers • Document reusable content approaches and contribute to lightweight style guides • Test and refine AI-generated content outputs and flag issues related to tone or clarity • Contribute example content for AI training and prompting