Senior Project Manager

We are looking for that rare candidate who can operate confidently in both worlds. You understand scope, schedule, budget, risks, vendors, governance, and executive reporting. You also possess the necessary data platform literacy—understanding data stacks, cloud platforms, data pipelines, warehouses, and BI tools—to scope programs accurately and have credible conversations with engineers. You are practical about where the organization is today and thoughtful about how to move teams forward without forcing process that does not fit the work. The ideal candidate communicates clearly, organizes complex technical work, secures commitments, manages risks, identifies the critical path, spots edge cases, reviews metrics and delivery data, and keeps stakeholders aligned. You continue to move forward in the face of ambiguity and imperfect information, creating enough structure for teams to make decisions, deliver outcomes, and improve how work gets done. What You’ll Take On Proactive Problem-solving: First and foremost you are a problem-solver. You work with data engineering teams, sponsors, and technical leads to keep work moving, remove blockers, escalate risks at the right level, and drive the best possible outcome for the business. Hybrid Delivery Leadership: You are comfortable leading through both traditional and agile delivery methods. You know when a project needs a clear plan, timeline, budget, RAID log, and governance rhythm, and when a team needs lighter agile planning, backlog refinement, Kanban flow, sprint routines, or iterative delivery checkpoints. Complex Data Project Ownership: You lead large, high-complexity data engineering and analytics initiatives from initiation through delivery, managing the integration of enterprise systems and cloud technologies at a program level. Cross-team Coordination: You coordinate work across multiple technical teams, business groups, vendors, and stakeholders. You identify dependencies early, clarify ownership, secure commitments, and help teams understand how their work connects to the larger strategic goals. Agile Enablement & Backlog Prioritization: You partner with Product Owners to prioritize the backlog. You help teams improve visibility, planning, and delivery health without adding unnecessary process, supporting backlog hygiene, intake practices, and practical delivery metrics. Efficient and Effective: You simplify where you can, protect engineering time, and use meetings, reporting, and documentation to help the team or stakeholders make better decisions. Exemplary Communication: Your written and verbal communication skills are strong. You can distill complex data pipelines and delivery details into clear updates for engineers, managers, sponsors, Steering Committees, and senior leadership based on the target audience. Risk, Issue, and Dependency Management: You proactively identify what could go wrong across complex, multi-team data programs before it becomes a problem. You surface risk early, drive mitigation plans, maintain clear decision records, and help stakeholders understand trade-offs. Stakeholder and Sponsor Partnership: You are a trusted partner to sponsors, technical leads, engineering managers, business partners, and PMO leadership. You can manage competing demands across multiple workstreams and make or facilitate hard trade-off decisions. Budget, Vendor, and Resource Awareness: You understand the financial and operational realities of enterprise technology delivery. You manage headcount allocation across programs, track budget variances, and support vendor coordination. Technical Credibility (Data Literacy): You are comfortable working with data teams across areas such as cloud platforms (e.g., AWS), data pipelines, warehouses, and BI tools. You do not need to be the technical expert, but you need enough understanding of the data stack to scope programs accurately, evaluate if plans are realistic, and have credible conversations with engineers. What You Bring Bachelor's degree in Information Systems, Business, Computer Science, Engineering, or a related field is preferred. Relevant experience may be considered in place of a degree. Minimum of 7 years of project or program management experience, with at least 4-5 years specifically in a data engineering, data management, or analytics environment. Data platform literacy — understanding of the data stack (cloud platforms like AWS or equivalent, data pipelines, warehouses, BI tools, etc.) to successfully manage data-centric projects. Proven experience leading large, complex, cross-functional projects with multiple teams, senior stakeholders, technical dependencies, and high business visibility. Strong project management foundation, including scope, schedule, budget, risk management (hands-on experience with RAID logs), issue management, dependency tracking, and stakeholder communications. Practical understanding of agile delivery methods, including Scrum, Kanban, Lean, backlog management, sprint or iteration planning, retrospectives, team metrics, and continuous improvement practices. Program management tooling — proficiency in Jira, Confluence, Smartsheet, or similar, with experience managing portfolio-level dependency tracking and documentation. Strong ability to partner with sponsors and technical leads, navigate ambiguity, manage difficult stakeholders, resolve conflict, and drive decisions without overstepping technical ownership. Experience with organizational change management, communication planning, implementation coordination, production readiness, and operational handoffs. PMP, PMI-ACP, CSM, PSM, SAFe, or similar certification is a plus, but hands-on delivery experience, technical credibility, business judgment, and strong communication are most important. Great to Have Previous experience as a Data Engineer or Data Engineering Manager What We Offer You Great Company Culture . Ranked as one of the most creative and innovative places to work, creativity, innovation,