Technical Debt Engineer

Position Summary:

The Technical Debt Engineer will help identify, organize, prioritize, and track technical debt across the organization, focusing on building a reliable data foundation, maintaining an accurate and trusted dashboard, and enabling execution against application rationalization and modernization goals.

This role requires a proactive, technically strong individual who owns the data layer — schemas, SQL logic, pipeline integrity, and Tableau reporting — while collaborating with program and leadership teams to keep the portfolio visible, accurate, and actionable. The ideal candidate has strong hands-on experience with SQL, relational databases (Postgres or similar), data pipelines, ETL, Tableau, and Git, and is comfortable working with cloud data platforms such as Snowflake as the program's data infrastructure evolves.

Key Responsibilities:

Tech Debt Strategy, Planning, and Execution:

Partner with business, product, and technology stakeholders to identify, document, and prioritize technical debt using TIME Classification and 6R frameworks.

Support the creation and execution of roadmaps for application migration, elimination, tolerance, and investment decisions.

Facilitate stakeholder discussions to clarify ownership, dependencies, migration destinations, effort sizing, timelines, and execution risks.

Track and follow up on actions, milestones, and roadmap commitments; keep portfolio data accurate and current.

Help prepare executive-ready materials communicating tech debt reduction progress, cost savings, and business value.

Dashboard, Reporting, and Visualization:

Own reporting and visualization solutions end-to-end – design, development, maintenance, documentation, and continuous improvement – using Tableau and related tools, ensuring views and reporting layers reflect accurate business logic, application categorization, and stakeholder needs.

Understand the full data ecosystem: analyze data across sources, identify meaningful relationships between systems and entities, and translate that understanding into accurate, trusted reporting logic and dashboard design.

Build and maintain trend and historical views so stakeholders can track real progress over time, detect drift, and evaluate whether interventions are working – not just a static current-state snapshot.

Support TCO and savings calculation design and implementation, including licensing, infrastructure, support, and maintenance cost data per application.

Maintain clear documentation of data sources, refresh processes, business logic, known limitations, and user guidance – complete enough that any team member can troubleshoot or extend the solution.

Research and Business Case Support

Evaluate internal and external tools, processes, and platforms to support strategic initiatives and inform technical decisions.

Support business case development with research, analysis, and data-backed recommendations.

Collaborate with cross-functional teams across Marketing, Finance, Revenue Operations, Security, product, engineering, and related functions to gather information, validate assumptions, and support informed decision-making.

Required Skills and Qualifications:

Experience in software engineering, data engineering, technical consulting, business technology, product operations, technology operations, or a related role.

Experience with Tableau dashboard development, including views, calculated fields, data source management, and dashboard maintenance.

Knowledge of the Salesforce technology ecosystem, architecture, and best practices.

Strong understanding of data definitions, data governance, data quality, and structured reporting.

Ability to analyze data across systems, identify meaningful relationships, and translate technical logic into clear, business-friendly language for stakeholders and leadership.

Excellent documentation skills, including the ability to explain technical logic, data flows, dashboard functionality, process context, and business impact.

Strong stakeholder management skills, including the ability to work with product, technology, business, data, and leadership teams.

Strong follow-up skills with the ability to track actions, owners, deadlines, dependencies, and progress.

Comfort using AI tools to support research, documentation, analysis, and productivity.