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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Infrastructure Analyst - **Company:** Focus LLC - **Location:** St. Louis, MO, United States - **Experience:** Expert - **Salary:** $70,000.0 - $90,000.0 - **Contract:** Permanent contract - **Skills:** Microsoft Excel, Microsoft Windows, Artificial Intelligence, Data Analysis, Asana, Audit Trail, Cloud Computing, Configuration Management Databases, Data Validation, Data Cleansing, Decision Support Systems, Statistical Hypothesis Testing, Identity and Access Management, Information Management, Information Technology Operations, Operational Data Store, Power BI, Microsoft Copilot, Microsoft SharePoint, Microsoft Power Automate, Powerquery, Tools for Reporting, Data Inconsistencies, Powerapps, Servicenow - **Published:** October 30, 2026 - **Apply:** https://www.careerbuilder.com/job-details/infrastructure-analyst-saint-louis-mi--5c690674-66ca-4f09-a588-5d37274d161f ## About the Role Analysis Skills, Decision Support, Operational Audit, Automation, Leadership, Process Analysis, Sales Qualification, Portfolio Analysis, Analysis Skills, Data Collection, * 5+ years of experience in a technology environment supporting operations, service management, reporting, process improvement, analytics, project coordination, portfolio support, or operational governance. * Working knowledge of IT operations, infrastructure services, ITSM practices, incident/request/change/problem processes, SLA/KPI concepts, ticket queues, operational dashboards, and service reporting. * Experience collecting, preparing, validating, analyzing, and presenting operational data from systems such as ServiceNow, Asana, Excel, Power BI, Power Platform, Microsoft 365, or similar reporting and work-management platforms. * Demonstrated ability to identify patterns, ask thoughtful questions, summarize findings, and translate data observations into practical recommendations or areas for deeper investigation. * Strong attention to detail and commitment to data quality, including the ability to identify missing information, stale records, unclear ownership, inconsistent categories, and unreliable assumptions. * Experience supporting process improvement, workflow analysis, documentation, backlog review, dashboard/report generation, action tracking, or portfolio governance activities. * Ability to communicate clearly in writing and verbally, including concise summaries, visuals, issue statements, trend narratives, and recommendation-oriented analysis. * High curiosity, learning agility, and interest in understanding how technology operations, processes, tools, data, automation, and AI can improve service delivery outcomes., * Experience with ServiceNow reporting, dashboards, Performance Analytics, ITSM data quality, catalog/workflow analysis, CMDB-adjacent operating data, or ticket trend analysis. * Experience with Asana, portfolio management tools, task/work tracking standards, backlog hygiene, dependency tracking, or project reporting. * Familiarity with Lean, Six Sigma, value-stream mapping, process mapping, process mining, ITIL Foundation, continual improvement, problem management, or operational excellence methods. * Experience using Microsoft Copilot, Power BI, Power Automate, Power Apps, Excel/Power Query, SharePoint, Teams, or other approved AI and automation tools to support analysis, reporting, and workflow improvement. * Experience supporting managed services partner governance, vendor performance reporting, SLA/KPI scorecards, QBR preparation, or service improvement action tracking. * Exposure to infrastructure domains such as network, systems/server, storage/backup, monitoring/event management, identity and access management, cybersecurity operations, cloud operations, or enterprise IT service delivery. * Ability to build simple, repeatable analytical models, dashboards, templates, process maps, and reporting routines that improve consistency and reduce manual effort. * Experience operating in environments requiring strong documentation, auditability, change discipline, data-quality standards, and clear decision/action tracking. ## Description The Infrastructure Analyst, Process, Automation & Decision Support supports the process excellence, portfolio governance, information management, and decision-support function within Infrastructure Operations & Architecture (IO&A). Reporting to the Sr. Manager, Process, Automation & Decision Support, this role collects, organizes, validates, and analyzes operational and portfolio data so IO&A leadership can identify patterns, evaluate improvement opportunities, and manage work with greater clarity and accountability. This role is responsible for much of the hands-on data collection, data preparation, reporting support, process mapping, backlog review, and analysis that enables the Sr. Manager to maintain the IO&A operating ledger, actively manage the Asana system-of-record portfolio, and produce decision-ready insight for leadership. The Analyst helps ensure operational work, improvement opportunities, assignments, risks, dependencies, and follow-up items are visible, current, and supported by reliable data. The Analyst works with ServiceNow incident, request, change, and problem data; Asana portfolio and backlog information; managed services performance data; and related operational artifacts to identify recurring demand patterns, bottlenecks, rework, aging work, handoff friction, automation candidates, tooling gaps, and opportunities to simplify service delivery. The role uses analytical discipline, curiosity, and AI-augmented productivity tools to accelerate discovery, test hypotheses, summarize findings, and suggest areas for deeper investigation under the direction of the Sr. Manager., Provide the practical analytical, reporting, data-quality, and process-mapping capability required for IO&A to understand operational performance, maintain portfolio visibility, identify improvement opportunities, and support automation, AI, and tooling enhancements that improve service delivery and management confidence., Enable IO&A to make better decisions and improve how work flows by collecting reliable data, identifying meaningful patterns, preparing actionable insights, maintaining quality in systems of record, and continuously learning how technology operations, service management, process improvement, automation, and AI can be applied to improve outcomes., 1) Collect, Prepare, and Validate Operational and Portfolio Data * Collect and prepare data from ServiceNow, Asana, dashboards, reports, meeting outputs, action logs, and other approved IO&A information sources. * Validate data completeness, consistency, assumptions, and source lineage before using information for analysis, dashboards, or leadership reporting. * Identify data-quality issues, inconsistent categorization, missing ownership, stale status updates, duplicate records, aging work, and other conditions that reduce confidence in system-of-record reporting. 2) Analyze ServiceNow Performance and Operating Patterns * Analyze ServiceNow incident, request, change, and problem data to identify trends, recurring demand drivers, bottlenecks, aging work, handoff delays, reopen/rework patterns, SLA/KPI concerns, change outcomes, and service-tower performance issues. * Prepare recurring operational analyses, trend summaries, root-cause themes, backlog views, and data-driven observations for review by the IO&A leadership team. * Connect operational data to practical improvement opportunities such as process changes, knowledge articles, runbook improvements, automation candidates, workflow enhancements, or clearer ownership rules. 3) Support IO&A Portfolio Governance and Asana Record Quality * Support the Sr. Manager in maintaining the IO&A Asana portfolio by reviewing active work, backlog items, milestones, owners, dependencies, risks, due dates, and status quality. * Help monitor adherence to portfolio data standards, intake expectations, status-reporting norms, taxonomy, ownership rules, and archival practices. * Prepare portfolio views that help leadership understand backlog trends, aging items, priority conflicts, capacity signals, delivery risks, and enterprise-impacting dependencies. 4) Support IO&A Operating Ledger, Actions, Decisions, and Accountability Tracking * Maintain and reconcile action logs, decision logs, assignment registers, follow-up items, risk/dependency trackers, and related operating artifacts under the direction of the Sr. Manager. * Ensure assignments have clear owners, due dates, status, next steps, and escalation points where appropriate. * Identify stale, unclear, or unowned items and elevate them for clarification so leadership cadences remain actionable and outcome-oriented. 5) Identify Process Improvement and Automation Opportunities * Use trend analysis, process mapping, value-stream thinking, and service-management practices to identify waste, friction, redundant steps, manual handoffs, unnecessary rework, and opportunities to simplify service delivery. * Document improvement opportunities with problem statements, supporting data, impacted processes, expected benefits, assumptions, candidate owners, and recommended next steps. * Help maintain the continuous improvement backlog by preparing candidate items for prioritization, measurement, and review by the Sr. Manager and relevant service owners. 6) Use AI and Automation Tools to Augment Analysis and Insight Generation * Use approved AI, Copilot, analytics, reporting, and automation tools to accelerate data exploration, summarize patterns, draft analysis narratives, generate hypotheses, and identify potential areas for deeper investigation. * Suggest practical AI, workflow, reporting, dashboard, or automation opportunities that could reduce manual effort, improve consistency, speed up analysis, or simplify IO&A service delivery. * Apply sound judgment, data validation, and human review when using AI-generated outputs; ensure recommendations are grounded in source data, operational context, and approved standards. 7) Prepare Dashboards, Reports, and Decision-Support Materials * Build and maintain recurring reports, dashboards, scorecards, data extracts, summaries, and visuals that support operational performance review, portfolio governance, managed services oversight, and continuous improvement prioritization. * Translate detailed data into clear findings, concise narratives, issue summaries, and recommended areas of focus for the Sr. Manager and IO&A leadership. * Support preparation of leadership-ready materials for operating reviews, monthly service reviews, QBR inputs, KPI discussions, backlog reviews, and improvement planning sessions. 8) Support Managed Services Partner Performance Measurement * Collect and analyze managed services performance data related to SLA/KPI compliance, backlog aging, ticket quality, runbook adherence, automation impact, escalation quality, change success, and continuous improvement commitments. * Assist with partner scorecards, improvement-action registers, QBR inputs, and trend narratives that help Technology Operations and the Sr. Manager evaluate partner performance and improvement opportunities. * Identify recurring partner-performance themes or data inconsistencies that should be reviewed by the Sr. Manager, Technology Operations, or service owners. 9) Maintain Learning Orientation and Build IO&A Analytical Maturity * Develop practical working knowledge of IO&A services, infrastructure domains, managed services operations, ITSM practices, portfolio management, process improvement, automation, AI, and reporting tools. * Approach analysis with curiosity, asking how processes work, why demand occurs, where friction exists, and what data is needed to make better decisions. * Continuously improve analytical methods, documentation practices, data-quality checks, and communication techniques so the team's insight generation becomes more repeatable, accurate, and useful over time. Behavioral Expectations (How this role operates) * Lead with curiosity. Seek to understand how processes, systems, teams, and work handoffs actually operate before drawing conclusions or recommending changes. * Protect data credibility. Validate source data, assumptions, definitions, and lineage so reports and recommendations can be trusted by leadership and operating teams. * Turn analysis into action. Do more than produce reports; identify what the data suggests, what questions should be asked next, and where improvement opportunities may exist. * Use AI thoughtfully. Use AI to accelerate analysis and learning while applying human judgment, source-data validation, and operational context before presenting findings. * Operate with disciplined follow-through. Keep action items, assigned work, backlog updates, and improvement candidates current so operating cadences produce outcomes rather than only discussion. * Communicate clearly and simply. Translate complex operational and portfolio data into concise observations, visuals, and recommendations that non-analyst stakeholders can understand and act on. * Stay growth-oriented. Demonstrate hunger to learn, expand technical and process knowledge, accept feedback, and build deeper capability across service management, automation, analytics, and IO&A operations. Key Deliverables * Validated data extracts, source-data notes, and data-quality observations from ServiceNow, Asana, and other approved IO&A systems of record. * Recurring ServiceNow analysis covering incidents, requests, changes, problems, SLA/KPI trends, backlog aging, reopen/rework, change outcomes, service-tower performance, and operational pattern identification. * Asana portfolio hygiene reviews covering active work, backlog items, ownership, due dates, milestones, dependencies, stale status, taxonomy consistency, and reporting readiness. * Operational trend summaries, root-cause themes, process-friction observations, automation candidate lists, and improvement opportunity briefs for Sr. Manager review. * Dashboards, reports, scorecards, visuals, and leadership-ready summaries supporting IO&A governance, operating reviews, managed services oversight, and continuous improvement prioritization. * Updated action logs, decision logs, assignment registers, improvement backlogs, risk/dependency trackers, and other operating artifacts maintained under Sr. Manager direction. * Managed Services Partner performance analysis inputs including SLA/KPI data, backlog trends, ticket quality observations, automation impact, runbook adherence, and improvement-action tracking. * AI-assisted analysis outputs, hypotheses, draft narratives, and automation/tooling suggestions that are reviewed, validated, and refined before use in leadership-facing materials.