Technical Program Manager

National Debt Relief, LLC.•,

4d•$135,000 - $155,500•Remote

About The Position

National Debt Relief is seeking a Technical Program Manager to bridge business needs and Data Engineering teams at National Debt Relief and its sister company, Reach Financial. Reporting to the SVP of Data Analytics & AI, this role owns how work enters, is prioritized, and moves through Data Engineering. The position serves as the primary intake point for requests, ensuring work is scoped and prioritized, stakeholders can track request status, and cross-team dependencies are identified early. The role helps the organization make informed trade-offs in a fast-moving environment. It requires technical understanding of a Snowflake-based data platform, an enterprise-level business perspective, and the confidence to challenge requirements and deadlines when needed. The Technical Program Manager partners with Data Engineering: the role provides business context and delivery structure while engineers provide technical expertise, with both parties determining where engineering capacity can deliver the greatest value. This position is available full-time. The stated salary range is $135,000.00–$155,500.00, with individual pay determined by work location, job-related skills, experience, and relevant education or training.

Requirements

At least 8 years of experience in technical project management, program management, or implementation management, including at least 2 years supporting data, analytics, or engineering teams.
Bachelor’s degree required.
Proven experience gathering requirements from non-technical stakeholders and translating them into well-scoped technical work with clear acceptance criteria.
Strong experience with Jira, including backlogs, epics, sprints, and workflows, and with a roadmap or work management tool such as Monday.com.
Experience managing dependencies, risks, and timelines across multiple teams.
Working technical understanding of data pipelines and data warehouse concepts, including ingestion, orchestration, transformation, data modeling, and data quality, sufficient to scope work, understand dependencies, and hold credible conversations with engineers.
Working knowledge of SQL sufficient to explore data, validate requirements, and confirm delivered work meets business needs.
Confidence and diplomacy in challenging requirements and deadlines, using capacity, data, and explicit trade-offs to reach agreement.
Business acumen and ability to understand and weigh the priorities of multiple business units at the organizational level.
Clear, concise written and verbal communication tailored to engineers, business stakeholders, and executive leadership.
Ability to partner collaboratively with Data Engineering, bring the business perspective to prioritization, and rely on engineers’ expertise to shape technical solutions.
Demonstrated proficiency with AI tools, including building repeatable workflows, providing actionable ticket context for AI coding agents, and verifying AI output against actual data and business needs.
Ownership mindset and strong organizational skills, including following work through delivery and keeping progress visible.
Computer competency and ability to work with a computer.
Ability to prioritize multiple tasks and projects simultaneously.
Punctuality and consistent attendance.
Ability to meet high monthly performance expectations.
Ability to work in a fast-paced, high-volume setting and navigate multiple computer systems while multitasking.
Ability to remain calm and professional during difficult discussions and take constructive feedback.
Availability for a full-time position.

Nice To Haves

Bachelor’s degree in Information Systems, Computer Science, Analytics, Business, or a related field.
Experience in a data warehouse environment, whether in data engineering, analytics, or management of data warehouse projects.
Familiarity with the modern data stack, such as Snowflake, dbt, Dagster, or Fivetran.
Agile, Scrum, or project management certification, such as CSM or PMP.
Experience in financial services or related industries.

Responsibilities

Serve as the primary intake point for data requests from stakeholders across National Debt Relief and Reach Financial, structuring how work is submitted, evaluated, and prioritized.
Refine requests into sprint-ready tickets with clear scope, acceptance criteria, dependencies, and business impact, written for engineers and AI coding agents.
Constructively challenge requirements and deadlines, clarify underlying business needs, distinguish genuine urgency from perceived urgency, and propose phased or alternative approaches when requests exceed available capacity.
Partner with Data Engineering leadership on sprint planning and the quarterly roadmap, balancing immediate business needs with platform reliability, technical debt, and longer-term business value.
Keep the Data Engineering roadmap and Jira epics accurate and current so priorities, timelines, and status are clear to leadership and stakeholders.
Coordinate deadlines and dependencies between Data Engineering and other departments, technology teams, and external vendors, surfacing risks and conflicts early.
Prioritize across both businesses by identifying shared priorities, duplicate requests, and opportunities to solve problems once for multiple teams.
Track delivery commitments and progress against engineering capacity, and proactively communicate status, scope changes, and timeline risks to stakeholders and leadership.
Continuously improve intake and delivery processes, including AI-assisted intake workflows, ticket standards, and templates.
Lead and supervise a team as needed, at the discretion of the business, to ensure program success.