Program Manager, Data & Analytics

CubeSmart; Northern (KY); Hybrid; USD 110,000 - 150,000; Full time

Job summary

CubeSmart is seeking a Technical Program Manager — Data & Analytics to own the IT data and analytics intake process in a hybrid role out of Malvern, PA. You will manage end-to-end data and analytics initiatives, translating business needs into well-scoped projects and ensuring consistent prioritization and delivery.

You will collaborate with Data Engineering, BI, Qlik, AI teams, and IT leadership, build scalable intake processes, and champion governance while enabling AI-driven analytics and

Qualifications

• Bachelor’s degree in a related field and 5–8 years PM experience.
• Minimum 2 years leading data, analytics, or BI projects.
• Experience managing a structured intake/requests process.
• Proficient with PM tooling (Asana preferred).
• AI literacy and comfort with AI/ML in projects.
• Ability to build process from scratch in a maturing PMO.

Responsibilities

• Own the Data Requests intake queue in Asana and define project briefs.
• Lead cross-functional planning with Data Engineering, BI, Qlik, and IT leadership.
• Identify risks, dependencies, and blockers; escalate as needed.
• Enforce IT PMO governance standards across the data portfolio.
• Support UAT planning and acceptance criteria with teams.

Skills

Stakeholder communication

Project management

AI literacy

Ambiguity handling

Cross-functional collaboration

Education

Bachelor's degree in Business, Information Systems, CS, Data Science, or related field

Tools

Asana

Jira

Monday.com

Databricks

Qlik

Job description

Overview

This is a hybrid role based out of Malvern, PA (3 days in office)

CubeSmart is seeking a Technical Program Manager — Data & Analytics to serve as the owner of our IT data and analytics intake process. This is a hybrid role based in Malvern, PA.

This role sits within the IT PMO and owns the end-to-end lifecycle of data and analytics project requests — from initial intake through prioritization, project planning, execution, and delivery. You will be the primary interface between business stakeholders and the technical data team (Business Intelligence, Qlik, and Data Engineering), ensuring that requests are well-defined, properly scoped, consistently prioritized, and tracked to completion in Asana.

The ideal candidate brings hands‑on experience leading data and analytics projects, working knowledge of modern data platforms (Databricks and Qlik), strong stakeholder management skills, and the discipline to build and maintain a structured intake process in an organization actively maturing its PMO practices. You are comfortable in ambiguity, energized by building process from scratch, and skilled at bridging the gap between business problems and technical solutions. You are AI‑ready — able to recognize where machine learning, generative AI, and predictive analytics create value, and comfortable leading projects that include AI/ML components. You are also AI‑enabled: you actively leverage AI tools in your own work to move faster, communicate more clearly, and deliver more consistent program outcomes.

This is a greenfield opportunity. You're building the process from the beginning, with IT PMO leadership and executive sponsorship behind you. If you thrive in environments where relationships matter as much as methodology and where your work has visible impact on how the organization makes decisions — and if you are excited about building a data program management practice that is ready for an AI‑driven future — this is the role for you.

Who we are:

At CubeSmart, we’re intentional about culture. You can experience it everywhere from our mission statement of “genuine care” to our “It’s What’s Inside That Counts” tagline to calling each other “teammates” rather than employees. This spirit fosters a fun and collaborative environment that has resulted in our rapid growth and being recognized amongst the top in our industry.

CubeSmart’s award‑winning team is made up of people who genuinely care. Teammates care about our customers and the life events and/or business needs they are facing. Teammates are passionate, responsible and understanding. The CubeSmart team is made up of people who have a can‑do attitude, are committed to their own success and the success of the company, and lead by example.

If this sounds like a team and culture that matches your personal values and motivations, we want to hear from you.

Responsibilities

Intake & Prioritization

• Own the Data Requests intake queue in Asana — the single front door for all data, analytics, reporting, and BI project requests across the organization.
• Partner with business stakeholders to translate requests into well‑defined project briefs, ensuring scope, business value, and success criteria are captured before work begins.
• Facilitate and lead bi‑weekly intake triage sessions with the data team; apply the PMO's Tier‑based prioritization framework to recommend sequencing.
• Maintain the integrity and hygiene of the Asana intake pipeline — statuses, stages, due dates, and ownership fields current at all times.
• Serve as the communication bridge between requestors and the data team: set expectations, provide status updates, and surface blockers early.

Project Planning & Execution

• Build and maintain project plans, timelines, and resource assignments for active data and analytics initiatives in Asana.
• Lead cross‑functional coordination across Data Engineering, BI, Qlik, business stakeholders, and IT leadership to plan and deliver data projects.
• Identify and proactively manage risks, dependencies, and blockers; elevate to the IT Prioritization Committee (IPC) when sequencing decisions are required.
• Enforce IT PMO governance standards — kickoff documents, impact analyses, decision logs, and post‑launch reviews — consistently across the data portfolio.
• Support UAT planning and acceptance criteria definition with the data team and business stakeholders.

Stakeholder Engagement & Process Rollout

• Drive adoption of the IT intake and prioritization process across business stakeholders — educating requestors on how to submit well‑formed requests and setting clear expectations.
• Build relationships with key business partners across Operations, Marketing, Revenue Management, Finance, and HR/Talent as their trusted PMO contact for data requests.
• Partner with IT PMO leadership to continuously improve the intake process, scoring model, and governance cadence as the organization maturing.
• Prepare and present regular portfolio status updates to the IT Prioritization Committee and Executive Steering Committee, including pipeline health, active project status, and capacity signals.

Data & Analytics Fluency

• Demonstrate working knowledge of the data project lifecycle — from data sourcing and pipeline development through reporting, visualization, and stakeholder delivery.
• Communicate effectively with Data Engineering, Databricks developers, and Qlik developers — understand enough technical context to scope work, identify risk, and ask the right questions.
• Partner with the data team to maintain a roadmap of foundational and recurring work (Qlik migrations, data pipeline upgrades, recurring reporting) alongside ad hoc requests.
• Maintain awareness of the evolving AI and machine learning landscape as it relates to data and analytics — understand when requests have AI/ML components, facilitate scoping conversations with the data team, and help stakeholders set realistic expectations for AI‑driven projects.
• Actively leverage AI productivity tools (such as generative AI assistants, AI‑powered documentation, and intelligent project management features) to improve intake quality, accelerate project planning, and enhance stakeholder communications.
• Contribute to the development of data governance and documentation standards as part of the broader PMO maturity roadmap.

Qualifications

Required

• Bachelor's degree in Business, Information Systems, Computer Science, Data Science, or a related field.
• 5–8 years of experience as a Project Manager, Technical PM, PMO Lead, or similar role — with at least 2 years specifically leading data, analytics, or BI projects.
• Demonstrated experience managing a structured intake or request management process across a cross‑functional team.
• Strong command of project management fundamentals: scope definition, scheduling, risk management, stakeholder communication, and status reporting.
• Proficiency with project management tooling — Asana, Jira, Monday.com, or equivalent; Asana experience strongly preferred.
• Demonstrated AI literacy: comfortable using AI tools in day‑to‑day program management work (documentation, synthesis, stakeholder communications, risk analysis) and able to hold a substantive conversation about where AI/ML fits within a data project.
• Comfortable operating in a maturing PMO environment — able to build process from scratch, navigate ambiguity, and iterate quickly.
• Exceptional stakeholder communication skills: able to translate technical constraints to business audiences and business priorities to technical teams.
• Strong organizational skills and demonstrated ability to manage multiple concurrent projects and priorities without dropping threads.

Preferred

• Hands‑on experience with Databricks — understanding of data pipelines, notebooks, and Lakehouse architecture is a meaningful advantage.
• Direct experience managing AI/ML projects or working alongside data science teams is highly valued.
• Hands‑on experience leading and delivering enterprise Business Intelligence (BI) initiatives using modern BI platforms such as Qlik, Power BI, or Tableau including the delivery of business capabilities, analytics solutions, and BI platform modernization programs.
• Familiarity with data warehousing, ETL/ELT pipelines, and cloud data platforms (Snowflake, AWS, Azure Synapse, or similar).
• PMP, PMI‑ACP, or equivalent project management certification.
• Experience rolling out a PMO intake or governance process to a change‑resistant audience.
• Direct or dotted‑line people management experience.
• Practical experience with Agile/Scrum or Kanban delivery alongside engineering and data teams.
• Exposure to real estate, retail, or self‑storage analytics — customer behavior, revenue management, operations reporting, or financial analytics.
• Working knowledge of IT infrastructure and cloud technologies.

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