Jobs at Chrysalis

Owns a major national wireless carrier account and its dealer network, serving as the executive-level relationship lead. Responsibilities include revenue growth, expansion, renewals, pricing and contract negotiations, platform and payments adoption, account reviews, dealer migrations, and issue resolution. The role coordinates internal product, delivery, support, and professional services teams while managing strategic relationships across corporate and independent dealer channels.

Lead enterprise sales conversations and product demonstrations for an AI-driven workforce management platform. Partner with sales and marketing to develop vertical go-to-market strategies, translate HR and hourly-workforce pain points into business cases, advise prospects on compliance and integrations, and provide customer and market insight to Product for roadmap decisions. The role requires a strong closer with extensive experience in enterprise, frontline, multi-location workforce environments.

Own enterprise client and prospect relationships, lead consultative product demos, support deal closing, and serve as a workforce and HR subject-matter expert. The role develops go-to-market strategies for specialty retail, partners with marketing on positioning, translates customer and market feedback into product opportunities, and advises Product on roadmap priorities, compliance, integrations, and hourly workforce needs.

Lead enterprise sales engagements for workforce and HR software, including prospecting support, consultative demos, deal closing, and go-to-market strategy. Advise prospects on hourly workforce operations, labor compliance, integrations, and retail pain points. Gather market feedback, shape product requirements and roadmap priorities, and translate operational needs into business cases. Partner across sales, marketing, customer success, and product while building a specialty-retail motion.

Design, build, and optimize cloud-native lakehouse data pipelines and curated data products using Python and SQL. Own data modeling, performance tuning, observability, governance, and reusable platform patterns to support analytics, embedded reporting, operational workflows, and AI/ML datasets. Mentor engineers, lead reviews, and improve platform reliability, cost efficiency, and data quality.

Design, build, and optimize cloud-native lakehouse pipelines and curated data products using Python and SQL. Own data modeling, performance tuning, observability, governance, and orchestration. Enable multi-tenant SaaS reporting, analytics, and AI-ready datasets; troubleshoot production issues; mentor engineers and drive platform architecture and reusable engineering patterns.

Design, build, and optimize cloud-native lakehouse pipelines and curated data products using Python and SQL. Own data modeling, performance tuning, governance, observability, and orchestration. Enable multi-tenant SaaS reporting, analytics, ML/AI-ready datasets, and near-real-time patterns. Mentor engineers, perform code and design reviews, troubleshoot production issues, and contribute to platform architecture and reusable engineering patterns.

Design, build, and optimize cloud-native lakehouse pipelines and curated data products using Python and SQL. Drive data modeling, governance, observability, performance tuning, and asset-based orchestration to support analytics, embedded reporting, operational workflows, and AI use cases. Mentor engineers, lead design/code reviews, and collaborate across product, engineering, and analytics to improve platform reliability, cost efficiency, and data quality.