Senior Systems Engineer, Commercial Intelligence and Analytics

What you'll do

• Own and maintain production systems that surface revenue performance, portfolio health, renewal dynamics, client opportunity, and service risk
• Design, build, and operate proactive insight pipelines translating recurring business needs into system architecture, data models, signal logic, and production-ready outputs
• Work with Business Technology and Revenue Operations to integrate intelligence outputs into dashboards, alerting systems, and operational workflows
• Build and deploy tools, signals, and automated deliverables to help teams prioritize effort, identify risk and opportunity, and act with greater precision
• Build trusted, production-grade data assets and pipelines using SQL, Python, validated metrics, and well-documented logic
• Integrate AI and LLM capabilities into systems and workflows to accelerate exploration, automate documentation, detect anomalies, and improve pipeline quality
• Translate ambiguous commercial problems into concrete technical plans, stakeholder-aligned requirements, and measurable deliverables
• Identify and prioritize scalable system investments that drive broad commercial impact
• Embed intelligence outputs into go-to-market systems and instrument delivery to assess signal effectiveness
• Raise the team’s engineering bar through rigorous documentation, automated testing, metric governance, and repeatable, version-controlled workflows

Requirements

• 5+ years of experience in analytics engineering, data engineering, software engineering, or a similarly systems-oriented role with strong quantitative foundations
• Strong SQL skills and experience working with large, complex datasets in modern data environments
• Proficiency in Python for building production systems, automation, and data pipeline development
• Strong foundation in software development practices including version control (Git), code review, testing, and CI/CD pipelines
• Experience translating business requirements into technical designs, system architecture, and production-ready deliverables
• Experience building durable, automated systems rather than relying on ad hoc or manual processes
• Demonstrated track record of identifying opportunities, proposing solutions, and independently driving systems, automation or technical initiatives from concept through adoption
• Experience operating in technical environments while collaborating with a broad set of internal stakeholders, including client-facing teams
• Familiarity with AI- or LLM-assisted tools and strong judgment in applying them responsibly and validating outputs to ensure accuracy, rigor, and reliability
• Strong written and verbal communication skills
• Strong attention to data quality, metric consistency, and engineering rigor

Tech stack

Benefits