Jellyvision

Business Development Rep

• Drive new business by setting meetings with qualified contacts at US employers
• Make 80-100 cold calls a day.
• Utilize Salesforce, Outreach, and Linkedin Sales Navigator with proficiency
• Craft high touch emails using excellent written communication skills
• Identify pain points through researching companies on Linkedin, Glassdoor, and company websites
• Set a minimum of 3-7 qualified meetings a week (depending on the territory and product.)
• Scout LinkedIn and other resources for contacts and research, adding anywhere from 30-50 new prospects into sequence per day
• Collaborate and communicate with your team and other departments to improves sales processes
• Report to designated manager to strategize more effective and creative sales methods
• Transform cold calls into something informative and delightful

Business Development Representative

Platform Engineer

• As a Senior Data Platform Engineer, you’ll be a hands-on engineer on a small, high-ownership data team.
• You’ll work across the full data platform - relational, warehouse, and lakehouse systems - building and operating the pipelines that power compliance, analytics, and reporting workloads.
• Design and build pipelines that move data across systems - supporting data lake ingestion, compliance workloads, and cross-domain data flows.
• Own pipeline operations end to end: monitoring, incident resolution, data quality, and documentation that lets any team member respond independently.
• Identify technical debt and reliability risks and raise them with clear context and proposed next steps.
• Design and maintain schemas across relational, warehouse, and lakehouse layers, working with application engineers and product to get data models right.
• Build out the platform’s service layer, infrastructure-as-code, and data quality frameworks - this role spans design and implementation.
• Keep platform documentation at a level where any team member can understand what exists, how it works, and where the risks are.
• Over time, contribute to the analytics engineering layer, including modeling practices and semantic layer development.
• Contribute to evaluations of the current platform against emerging architectures and tooling, helping produce trade-off analyses and recommendations.
• Bring what you see day to day in the systems you operate into the team’s improvement roadmap and technical direction.
• Track and report on platform health metrics: pipeline uptime, failure rates, data freshness, and cost trends.
• Mentor peers and junior engineers through code review, pairing, and technical guidance.