Data Integrity Manager

United Airlines•Chicago, IL

1d•$102,220 - $133,194•Onsite

About The Position

Achieving our goals starts with supporting yours. Grow your career, access top-tier health and wellness benefits, build lasting connections with your team and our customers, and travel the world using our extensive route network. Come join us to create what’s next. Let’s define tomorrow, together. Description Caring is one of United’s most important principles. And no one exemplifies that more than our Customer Contact Center team, who helps our customers with everything from booking and managing reservations, to questions about their travel, MileagePlus accounts, and so much more! Are you a people person? Do you get fulfillment from helping others? Then join a team that cares for our customers and makes a positive impact on their travel experience, every single day.

Requirements

Bachelor's degree or related experience
Management Information Systems, Data Science, Informatics, or a related field that is heavily analytical/systems-driving discipline
Enterprise content/knowledge management certification or a formal data governance credential
3+ years of experience managing enterprise data quality, master data management (MDM), or content/knowledge base architectures
2+ years working directly within or supporting a complex contact center technology stack
Deep expertise in structuring content for optimal search, reuse, and machine consumption
Understanding how to transition from long-form text documents to modular, snippet-based data structures
High literacy regarding how data travels from backend systems to front-end chat/voice interfaces
Ability to trace complex customer journey across disparate legacy backends and identify where data silos will break automated conversations
Familiarity with Generative AI concepts and prompt writing
Exposure to AI platforms such as Copilot, ChatGPT, Gemini, Claude, Perplexity, and NotebookLM
Must be legally authorized to work in the United States for any employer without sponsorship
Successful completion of interview required to meet job qualification
Reliable, punctual attendance is an essential function of the position

Nice To Haves

Master's degree or related experience
Master of Science in Data Governance, Business Analytics, Knowledge Management or equivalent field
Data infrastructure certification or platform certification in enterprise knowledge management tools
Direct experience preparing corporate data or content management architectures for a large-scale Conversational AI, LLM, or automated self-service deployment that achieved significant deflection/containment metrics
Strong conceptual understanding of semantic search function to ground LLMs and reduce AI hallucinations
Familiarity with how data is logged, stored, and routed within major platforms
AI ethics on string-masking, tokenization, or hashing to protect sensitive customer data at point of intake
Hands-on experience using AI tools in projects, internships, or work environment
Knowledge of automation platforms such as Power Automate, Copilot Studio, Zapier, or n8n

Responsibilities

Redesign traditional, human-readable knowledge articles and FAQs into structured, modular data blocks optimized for retrieval-augmented generation (RAG) and semantic search used by Generative AI and agentic
Ensure a single source of truth across all channels
Establish and enforce strict data quality, deduplication, and standardization rules for customer profile data, transaction histories, and interaction metadata
Ensure that standard data is sanitized and formatted across systems so AI models can accurately read and interpret
Partner direction with digital technology, customer profile, and data scientists to map out data dependencies required for automation. Audit production journeys to understand real-time experience, latency issues, response accuracy, ability to read/write to internal systems, and enabling automation to perform transactions
Create a robust feedback loop by analyzing automated ‘fallbacks’ or classification failures caused by data gaps. Review transcripts and system logs to identify missing or inaccurate knowledge articles, broken data fields or unmapped backend logic, continuously tuning the data layer to drive customer resolution
Collaborate with Information Security and other privacy teams to ensure channels strictly comply with privacy regulations and manage data-masking rules to prevent personally identifiable information (PII) from leaking into LLM training logs or unauthorized third-parties