
1001 - 5000 employees
Founded 1999
🛒 Retail
💸 Finance
💳 Fintech
Retail • Finance • Fintech
Progressive Leasing is a company that offers lease-to-own purchase options for consumers who may have less-than-perfect credit. They provide a convenient and flexible way for customers to acquire items such as furniture, electronics, jewelry, tires and wheels, mobile devices, appliances, and mattresses from thousands of retail locations nationwide. Their underwriting process considers various data points like income and banking history instead of relying solely on credit scores, allowing more people to be approved. With automatic payment scheduling options, customers can align payments with their paydays, enhancing ease and affordability.
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1001 - 5000 employees
Founded 1999
🛒 Retail
💸 Finance
💳 Fintech
Retail • Finance • Fintech
Progressive Leasing is a company that offers lease-to-own purchase options for consumers who may have less-than-perfect credit. They provide a convenient and flexible way for customers to acquire items such as furniture, electronics, jewelry, tires and wheels, mobile devices, appliances, and mattresses from thousands of retail locations nationwide. Their underwriting process considers various data points like income and banking history instead of relying solely on credit scores, allowing more people to be approved. With automatic payment scheduling options, customers can align payments with their paydays, enhancing ease and affordability.
• Maintain and improve delivery visibility across complex, dependency-heavy work by tracking cross-team blockers, integration risks, and upstream/downstream exposure • Model the impact of scope changes, timeline shifts, and capacity constraints by presenting structured options with clear trade-offs to decision-makers • Drive backlog readiness discipline, ensuring work entering execution is well-defined and dependency-mapped before it starts • Identify and actively manage delivery risk through surfacing issues proactively, quantifying impact, and framing resolution paths for engineering and product leadership • Maintain and improve delivery operating norms that reduce rework, carryover, and execution variability over time • Leverage AI tooling to accelerate operational work, including status synthesis, risk narrative generation, and backlog readiness summarization, while maintaining human judgment on prioritization and stakeholder framing decisions. • Influence engineer and product manager behavior through structure and data by driving accountability and shared clarity on delivery commitments • Frame delivery trade-offs clearly by presenting structured options with explicit implications on timeline, quality, and capacity • Partner with Product Managers to enforce readiness standards and protect delivery integrity when scope pressure mounts • Communicate delivery feasibility and confidence clearly to the engineering team and partnering Project Managers by providing early warning when assumptions change and surfacing recovery options when they do • Socialize production release schedules in advance with the development team, Product Manager, and relevant change advisory processes ensuring the team is prepared for releases • Maintain working fluency in the technical systems your team supports through a solid understanding of integration surfaces, API dependencies, and release risk in context • Coordinate across engineering, QE, architecture, and platform teams to manage cross-functional dependencies and resolve blockers at the right level • Apply delivery metrics (i.e. cycle time, throughput, carryover, predictability) as operational signals that drive structural change in how the team works • Manage a Kanban-based delivery system for a team handling a mix of planned work and high-priority operational demand • Balance intake discipline with responsiveness by maintaining flow efficiency while protecting planned delivery commitments from reactive work pressure • Model WIP impact and context-switching costs to protect team throughput and focus • Maintain and improve intake and triage processes that bring structure to interrupt-driven work without creating bureaucratic overhead • Monitor Kanban flow metrics (i.e. lead time, cycle time, and queue depth) to identify bottlenecks and maintain healthy throughput • Coordinate with dependent teams and platform consumers to maintain demand visibility and set clear expectations proactively • Manage sprint cadence and iteration health across one or more engineering teams with a focus on commitment reliability and sprint goal integrity • Enforce sprint entry discipline by ensuring stories meet sizing and readiness standards before planning begins, and holding the line when they don’t • Track and improve sprint predictability using carryover, velocity trends, and planning accuracy as signals to adjust how the team operates • Manage scope pressure during active sprints through modeling the impact of additions or changes and presenting clear trade-off options to the Product Manager before commitments shift • Maintain cross-sprint dependency visibility across teams or workstreams, identifying what is at risk and when • Run retrospectives as structured operational reviews by identifying systemic delivery friction and driving follow-through on changes
• 5 to 7 years of delivery management experience embedded within software engineering teams in a fintech or similarly regulated, technically complex environment • Demonstrated ability to influence engineer and product manager behavior through structure, data, and clear framing • Proven experience building or materially improving delivery systems: reducing carryover, improving commitment reliability, or increasing planning quality through structural changes • Experience modeling delivery trade-offs and presenting structured options to leadership • Deep SDLC fluency, including integration complexity, release management, dependency modeling, and cross-team coordination • Strong working knowledge of Jira for dependency tracking, delivery modeling, and operational insight • Comfort operating in API-heavy, integration-dependent backend environments where delivery risk lives in the connections between systems • Prior experience managing Kanban-based teams in service-oriented or platform engineering environments • Demonstrated use of flow metrics (i.e. lead time, cycle time, WIP) as day-to-day operational tools for managing team health and throughput • Demonstrated use of AI-assisted tooling (LLMs, AI-augmented Jira workflows, or similar) to improve delivery throughput, reduce coordination overhead, or accelerate artifact generation with the discernment to know when AI output requires human review before it reaches stakeholders. • Calm, structured approach to ambiguity and able to reset expectations and protect delivery integrity when plans change • Strong written and verbal communication skills, including the ability to frame engineering consequences clearly for non-technical stakeholders • Bachelor’s degree or equivalent experience.
• Full Health Benefits; Medical/Dental/Vision/Life Insurance + Paid Parental Leave • Company Matched 401k • Paid Time Off + Paid Holidays + Paid Volunteer Hours • Employee Resource Groups (Black Inclusion Group, Women in Leadership, PRIDE, Adelante) • Employee Stock Purchase Program • Tuition Reimbursement • Charitable Gift Matching • Job required equipment and services
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