Jobs at Cognism

Leads Cognism’s global revenue operations strategy across Sales, Marketing, and Customer Success. Responsibilities include revenue planning, forecasting, quota and territory design, process optimization, technology enablement, analytics, cross-functional alignment, and global team leadership. The role drives operational efficiency, scalable growth, accountability, and data-informed decision-making while managing revenue technology including Salesforce, Seismic, HubSpot, Looker, Tableau, Gong, and Outreach.

Lead DACH enterprise and mid-market demand generation strategy, ABM execution, integrated campaign planning, and pipeline creation. Partner with sales, RevOps, paid media, content, web, brand, and events teams to build and optimize multi-channel programs. Own campaign objectives, budgets, reporting, attribution, and performance against MQL, SQL, pipeline, revenue, and account engagement targets.

Owns day-to-day Deal Desk operations within Revenue Operations, managing CPQ approval queues, complex deal reviews, governance, audit trails, reporting, and process improvements. Partners with Sales, Finance, Legal, Security, Compliance, and executive stakeholders to resolve non-standard transactions, improve commercial policies, automate workflows, and provide actionable insights on pricing, discounting, contracts, and deal quality.

Acts as a strategic and operational partner to the VP of Product Engineering. Coordinates cross-functional initiatives, executive communications, organizational planning, board materials, dashboards, KPIs, and decision accountability. Tracks risks and dependencies, supports organizational design and hiring, improves processes through automation and AI, and represents leadership in selected meetings. Success involves predictable initiative delivery, stronger operating cadence, executive reporting, and improved organizational execution across Engineering, Product, Finance, and HR.

Design and develop backend services, APIs, CRM integrations, enrichment workflows, and synchronization services. Own software through production, improve reliability and performance, write automated tests, participate in reviews and architecture discussions, and collaborate with Product, Customer Success, Data Engineering, and Platform teams. The role involves AWS, microservices, Kafka, databases, CI/CD, and production support.

Build and operate Cognism’s AWS cloud platform, including Kubernetes infrastructure, Infrastructure as Code, CI/CD pipelines, observability, automation, incident response, and reliability improvements. Partner with engineering, security, and architecture teams to improve resilience, developer productivity, and cloud cost efficiency. The role requires hands-on production platform engineering experience, strong Kubernetes administration, deployment automation, scripting or programming skills, and excellent English communication.

Build and maintain cloud-native backend services supporting Data-as-a-Service, REST APIs, and Model Context Protocol capabilities. Design distributed microservices, deliver reliable production software, own features from technical design through operational support, write automated tests, contribute to architecture, collaborate across engineering and product teams, and mentor less experienced engineers.

Staff Software Engineer responsible for architecture and technical ownership of Cognism’s distributed DaaS, API, MCP, and enterprise integration platforms. The role includes setting engineering standards, driving scalable and reliable backend architecture, mentoring senior engineers, advising leaders, and influencing technical decisions across multiple teams. The engineer will help establish Cognism’s Warsaw Engineering Hub and deliver production capabilities that improve platform reliability, scalability, and development velocity.

Generate outbound meetings via calls, emails, social outreach and research; engage C-suite and director prospects; qualify leads through discovery; share tailored content; manage pipeline in Salesforce; collaborate with BDMs to convert opportunities; continuously learn and maintain a resilient, results-driven mindset.

Drive full-cycle enterprise SaaS sales by prospecting, building pipeline, managing complex multi-stakeholder deals, engaging C‑level buyers, executing territory plans, delivering tailored demos/proposals, collaborating with cross-functional teams, and meeting quota through new logo acquisition and account expansion in the U.S. market.

Drive full-cycle enterprise SaaS sales for Cognism’s B2B sales intelligence platform. Prospect and build pipeline, manage complex multi-stakeholder sales cycles, cultivate executive-level relationships, execute territory plans, deliver tailored demos and proposals, collaborate cross-functionally, and contribute to U.S. GTM strategy while meeting revenue and quota targets.

Design and deliver targeted training and enablement for German-speaking customers, partnering with Account Managers to drive adoption, retention, and expansion. Create scalable learning assets, run outcome-focused sessions, diagnose adoption gaps, and feed insights back to Product and Revenue teams to improve customer outcomes.

Lead and develop a team of Solution Consultants to design scalable, measurable solutions that accelerate time-to-value and protect revenue. Drive structured discovery, shape complex customer use cases, reduce adoption risk, and partner cross-functionally with Sales, CS, Product, and RevOps. Coach the team, embed solution standards, and step into strategic accounts as needed to support expansion and retention.

Design and run onboarding and ongoing enablement programmes for SDRs, AEs, and AMs; create playbooks, training, and content; align tools and adoption with RevOps; collaborate with Product and Marketing; track and improve sales performance metrics.

Identify and generate new business opportunities via outbound calls, emails, social outreach and research; engage C-suite and director-level prospects; qualify leads through discovery; manage pipeline in Salesforce; collaborate with BDMs to convert opportunities; deliver tailored content; and continuously learn to improve performance in a fast-paced sales environment.

Build and maintain automated ML pipelines, design training and deployment infrastructure, implement secure scalable AWS architectures, enforce MLOps best practices, collaborate with data scientists, bridge engineering and DevSecOps, and monitor production ML services for reliability and performance.