Application Support Analyst (Smyrna)

OVERVIEW This role sits at the center of PowerPlan’s customer experience, combining technical problem‑solving, customer communication, and product expertise to help customers achieve their business goals. You will work hands‑on with complex enterprise software, troubleshoot real customer issues, and grow into a trusted technical advisor. The role offers meaningful exposure to financial systems, scalable enterprise platforms, and emerging AI‑enabled tooling in a mission‑critical environment.

COMPANY For more than 30 years, PowerPlan has helped North American energy and utility organizations make confident financial decisions that improve lives and power the world. Our software is trusted by CFOs and finance leaders to manage complex assets, regulatory requirements, and financial processes at scale. We value collaboration, accountability, continuous learning, and a strong commitment to customer success.

KEY PERFORMANCE OBJECTIVES (First 12–18 Months) 1: Deliver Reliable, High‑Quality Customer Case Resolution (First 6 Months) Outcome: Within the first 90 days, complete Support’s technical and functional onboarding program and independently resolve 80–85% of assigned customer support cases within defined SLAs while maintaining less than 5% overdue cases. By six months, consistently balance case volume, resolution speed, and documentation quality across a varied and growing support workload. Impact: Reliable case resolution protects customer trust, reduces escalations, and enables the support organization to scale efficiently while maintaining service quality.

How: Triage and prioritize cases effectively, apply structured troubleshooting, document root causes and resolutions clearly, communicate status proactively, and escalate appropriately when complexity or risk requires it. 2: Resolve Complex Technical Issues Through Strong Root Cause Analysis (First 12 Months) Outcome: Within six months, independently analyze and resolve at least one complex customer issue per week requiring code‑level investigation (e.g., PowerBuilder, SQL, .NET, PL/SQL). By twelve months, handle high‑severity technical issues end‑to‑end with minimal reliance on senior escalation. Impact: Strong root cause analysis reduces repeat incidents, shortens time to resolution for critical issues, and improves overall product stability.

How: Investigate application code, logs, and data flows; reproduce issues where possible; apply disciplined analytical techniques; collaborate with engineering when needed; and document findings for reuse. 3: Own Customer Communication and Satisfaction Throughout Issue Resolution (First 12 Months) Outcome: Consistently provide clear, proactive communication for all assigned cases, achieving an average customer satisfaction rating of 4.5 or higher. Over time, be recognized as a reliable point of contact who owns issues end‑to‑end, including escalations. Impact: Strong communication reduces customer frustration, builds trust during complex resolutions, and strengthens long‑term customer relationships.

How: Set expectations early, provide regular updates, explain technical issues in customer‑appropriate language, coordinate across teams, and confirm satisfaction after resolution. 4: Build Product Expertise and Leverage Knowledge to Elevate Team Performance (First 12 Months) Outcome: Within nine months, develop deep expertise in one to two PowerPlan products or modules, enabling independent resolution of most module‑specific issues. By twelve months, contribute at least five reusable knowledge assets and actively support peers through mentoring and escalation assistance. Impact: Shared expertise improves consistency, reduces dependency on senior resources, and raises overall team capability.

How: Study product architecture, review historical cases, document recurring solutions, participate in knowledge‑sharing forums, and support peers during complex investigations. 5: Leverage AI and Machine Learning Tools to Improve Support Effectiveness and Insight (First 12–18 Months) Outcome: Adopt and apply AI‑enabled tools and machine learning techniques to enhance support workflows, improve anomaly detection or diagnosis, and generate actionable insights from customer and system data. Impact: Thoughtful AI adoption improves efficiency, enables earlier detection of systemic issues, and supports scalable, high‑quality enterprise support. How: Apply appropriate ML techniques, explore NLP use cases for support data, collaborate with product or data teams, and evaluate outputs using sound validation and performance metrics.

WHAT YOU BRING Experience resolving customer support issues in enterprise software environments with strong SLA and documentation discipline Solid technical foundation across databases, application architectures, and debugging tools (SQL, PowerBuilder, .NET, PL/SQL) Strong written and verbal communication skills with a customer‑first mindset Ability to analyze complex systems methodically and identify true root causes Experience developing deep product or module expertise and sharing knowledge with peers Preferred: Experience with AI or machine learning projects, including supervised or unsupervised learning techniques; familiarity with ML libraries such as scikit‑learn, TensorFlow, PyTorch, or Keras; exposure to NLP techniques; and experience working with data pipelines, feature engineering, or model evaluation—especially in financial, anomaly detection, or enterprise software contexts