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Lead enterprise Alation deployments for regulated industries, advising stakeholders on data and AI governance, data quality, metadata, lineage, compliance, and business value. Diagnose governance gaps, conduct discovery sessions, demonstrations, workshops, implementations, and adoption programs. Define KPIs, present outcomes to executives, and partner with account teams on expansion opportunities. The role requires significant consulting and data management experience, industry expertise, and 25–40% customer travel.

Leads customer-facing development of AI agent systems, multi-agent workflows, BI and ML pipelines, and enterprise data governance solutions. Partners with Fortune 500 stakeholders to translate business and data challenges into production-grade technical solutions, develops reusable delivery patterns and internal tooling, influences product roadmaps, conducts competitive analysis, and mentors engineers and technical teams.

Creates high-quality enterprise sales pipeline through AI-powered, account-based outbound prospecting. Researches accounts, identifies buying signals, personalizes multichannel outreach, conducts discovery conversations, and partners with account executives and sales leaders on strategic account plans. Uses Salesforce, Gong, Outreach, Orum, LinkedIn Sales Navigator, ZoomInfo, 6sense, intent data, and AI tools to prioritize prospects, optimize messaging, and improve conversion. The role is hybrid, requiring three days weekly in the Redwood City office.

Lead complex customer deployments involving data intelligence, AI agents, and governance. Responsibilities include discovery, solution architecture, low/no-code prototyping, end-to-end delivery, stakeholder facilitation, risk management, value realization, executive business reviews, expansion support, and creation of reusable deployment patterns. The role requires hands-on SQL and technical fluency while serving as a strategic advisor to senior customer stakeholders.

Design and prototype AI agent systems, agentic workflows, BI and ML pipelines, and enterprise data solutions for strategic customers. Translate governance needs into technical roadmaps, deliver measurable business value, create reusable implementation accelerators, and provide technical guidance to customers and junior engineers. Collaborate with Deployment Strategists, Account Executives, Product, Engineering, and GTM teams to improve Alation’s platform and customer outcomes.

Drives customer evaluations and deployment progress by tracking technical issues, coordinating account teams and internal stakeholders, supporting RFIs and RFPs, translating customer requirements into product feedback, delivering focused solution demonstrations, and documenting reusable knowledge. The role requires strong organization, communication, technical presentation skills, and familiarity with data, AI, databases, analytics, integration, cloud platforms, and related technologies.

Lead and scale an inside sales team for Commercial accounts ($1B-$10B), owning new and expansion ARR, NRR and GRR. Hire, coach, forecast, sell alongside reps, run renewals, implement MEDDPICC and account plans, partner with cross-functional teams, and adopt AI-native sales tooling to drive repeatable, metrics-driven growth and forecast accuracy.

Build frontend code for Alation’s AI-powered data intelligence product while applying strong UX and design judgment. Collaborate with product managers and engineers on copilot interactions, data visualization, and generative workflows. Improve component consistency, information hierarchy, progressive disclosure, and usability; resolve ambiguous product problems; and iterate based on team and user feedback. The role is hybrid in Redwood City, California, two days per week, and offered as a full-time contract with potential contract-to-hire.

Drive new logo acquisition and expansion within an enterprise territory by leading complex, multi-stakeholder SaaS sales cycles. Advise executives on data, governance, analytics, and AI strategy; build strategic account plans; manage pipeline and forecasting; collaborate with cross-functional teams and partners; and leverage AI tools to improve selling effectiveness.