Back to search
About AuxoAI
AuxoAI helps enterprises transform how they operate by combining business consulting, data, engineering, and Agentic AI. We are building an AI-native consulting model in which every team member is expected to use AI thoughtfully to improve speed, insight, quality, and client outcomes.
What You Will Do
路 Maintain the integrated delivery plan for data migration, conversion, cleansing, reconciliation, and validation activities.
路 Coordinate business data owners, source-system teams, data engineers, functional teams, testing teams, and the System Integrator.
路 Track data objects, conversion cycles, mock loads, entry and exit criteria, defects, reconciliations, and business sign-offs.
路 Manage dependencies between source extraction, transformation rules, Oracle load processes, downstream validation, and cutover sequencing.
路 Facilitate data readiness reviews and drive resolution of quality, mapping, ownership, timing, and environment issues.
路 Prepare concise status reporting on conversion progress, data quality, open defects, reconciliation results, and readiness risks.
路 Support SIT, UAT, business simulation, cutover rehearsals, production migration, and hypercare validation.
路 Ensure decisions, assumptions, mapping changes, and unresolved data issues are traceable and assigned to accountable owners.
AI-Enabled Delivery Responsibilities
路 Use AI to summarize mapping documents, identify conflicting transformation rules, and highlight incomplete data ownership decisions.
路 Generate AI-assisted conversion status narratives, reconciliation summaries, defect themes, and data-quality risk insights.
路 Apply AI to compare source-to-target specifications, workshop decisions, and test evidence for traceability gaps.
路 Develop repeatable prompts or workflows that improve the speed and consistency of data PMO activities.
Common AI-First Expectations at AuxoAI
路 Use enterprise AI tools such as ChatGPT Enterprise, Claude Enterprise, Gemini, or equivalent platforms to accelerate delivery and improve decision-making.
路 Apply AI to automate meeting summaries, action-item tracking, status reporting, executive communications, and document synthesis.
路 Use AI-assisted analysis to identify delivery risks, cross-team dependencies, emerging bottlenecks, and areas requiring leadership attention.
路 Continuously identify PMO activities that can be simplified, standardized, or automated through AI and workflow automation.
路 Validate AI-generated outputs for accuracy, confidentiality, traceability, and business relevance before they are used in program decisions.
路 Collaborate with consulting, data, engineering, and AI teams to pilot and scale AI-enabled delivery practices across the program.
Requirements
路 4-6 years of experience in project coordination, project management, data delivery, or enterprise transformation.
路 Understanding of data migration concepts including extraction, cleansing, mapping, conversion, validation, and reconciliation.
路 Experience coordinating cross-functional teams and tracking milestones, dependencies, risks, issues, and decisions.
路 Strong Excel, documentation, analytical, and communication skills.
路 Ability to translate technical data issues into clear business and program impacts.
路 Comfort using AI tools to analyze documents, summarize findings, and improve reporting.
Preferred Qualifications
路 Experience with Oracle Fusion data conversion, FBDI, ADFdi, or related Oracle data-load methods.
路 Exposure to SQL, ETL/ELT, Snowflake, Informatica, Oracle Integration Cloud, or similar platforms.
路 Experience supporting mock conversions, reconciliations, SIT, UAT, or cutover.
路 Experience with Jira, Azure DevOps, Power BI, Tableau, Smartsheet, or Microsoft Project.
路 Familiarity with data governance, data quality, and master data management.
What Success Looks Like
路 Clear delivery visibility
路 Early risk identification
路 Responsible AI adoption
路 Predictable workstream outcomes
Learn more about this Employer on their Career Site
