Top Tech Jobs & Startup Jobs

Manage ServiceNow transformation projects end-to-end: create project charters, sprint and release plans, facilitate workshops, drive stakeholder communication, adoption, and value realization. Partner with product managers to develop roadmaps and ensure delivery using Agile and scaled frameworks across global IT teams.

Lead design and delivery of a federated Integration Platform for developers and data teams. Build self-service onboarding, secure provisioning, telemetry and dashboards, standards and reusable contracts, CI/CD automation, and developer-facing workflows. Balance security, usability, and scalability while partnering with architects, platform owners, and engineers to iterate quickly and improve developer experience.

Partnership-focused senior analyst who turns internal and external data into actionable commercial and marketing insights. Designs dashboards, monitors KPIs and campaign performance, leverages advanced analytics and predictive outputs, collaborates with data science and IT, ensures data governance and compliance, and mentors junior analysts while enabling cross-functional stakeholders.

Design, develop, and govern enterprise ontologies, OWL/RDF semantic models, vocabularies and taxonomies to provide consistent, discoverable data context. Collaborate with product, engineering, and domain experts to map sources, validate models, support integration with knowledge graphs and AI/agentic systems, and establish standards, versioning, and governance for production-ready semantic assets.

Support GPVCM KPI tracking (quality, compliance, productivity, trainings); assist with month-end reporting, inventory tasks, and logistics activities. Perform data entry, reporting and document management; provide technical support and training as needed.

Lead product definition and roadmap for a Data Context Layer capability enabling standardized self-service publishing, discovery, and consumption of data context. Partner with engineering, enterprise architecture, governance and platform teams to deliver scalable, governed context services that support AI/agentic workflows, metadata/ontology use, adoption, release readiness, and operationalization.

Architect and implement an enterprise Data Context Layer to publish, discover, and consume standardized context. Define integration patterns, access control, versioning, lineage, observability, and production-grade deployment. Enable both human and agentic AI consumers through semantic models, ontologies, knowledge graphs, APIs, and reference implementations while supporting governance, security, and engineering teams.

Lead product definition and delivery of a Data Context Layer's Context & Semantics capabilities. Define context models, semantic standards, and reusable building blocks to enable governed, interoperable data and agentic AI workflows. Align with enterprise architecture and platforms, drive cross-product adoption, partner with engineering for scalable implementations, and ensure execution via roadmaps, milestones, and stakeholder alignment.

Drive onboarding and early adoption of an enterprise Data Context Layer by guiding users through setup, identifying initial high-value use cases, delivering enablement materials and sessions, removing adoption barriers, tracking activation metrics, and collaborating with product, engineering, and governance teams to improve activation and support agentic AI workflows.

Provide first-line automation support and troubleshooting for manufacturing lines and packaging systems. Lead quality investigations, corrective/preventive actions, GMP-compliant documentation, change controls, and qualification activities. Partner with operations, quality, and maintenance to implement continuous improvement and ensure automation system integrity and compliance (SLC, cGMP, safety).