Business Systems Analyst

Your Job

Koch Technology is seeking a Business Systems Analyst to join our LIFT product team in a role focused on automation, applied analytics literacy, and AI enablement.

This role sits at the intersection of business process understanding and technical enablement; working closely with stakeholders to identify opportunities, clarify requirements, and translate them into scalable automation and analytics solutions.

The BSA is responsible to accelerate analytics, automation, and insight delivery by selecting the right tool for the problem (Copilot, Databricks, Fabric, etc.), establishing repeatable patterns, and enabling others to work differently.

Early in the role, the expectation is that roughly 50% of time is spent on discovery, experimentation, and establishing patterns, intentionally maturing toward execution, repeatability, and sustained delivery.

Our Team

The Koch Facilities Enablement Team supports LIFT (Land, Infrastructure, Facilities, Transactions); and the teams leveraged enterprise applications and surrounding technology that enables Facilities business processes and data-driven decision making.

Location: This role can be located in Wichita, KS / Atlanta, GA / Plano, TX and requires an in office presence with flexibility

This role is not eligible for VISA sponsorship

What You Will Do

Discovery & Experimentation:



* Partnering with business and product stakeholders to understand processes, decision points, and pain areas


* Running structured experiments to improve cycle time, clarity, and quality in analytics, reporting, or workflows


* Evaluating tools (Copilot, Databricks capabilities, Fabric, workflow automation, or integrations), selecting the right approach based on the problem and expected outcome, not habit


* Translating experimentation outcomes into documented patterns, recommendations, or next-step options

Accelerating Insights & Sustainable Enablement:



* Partnering with LIFT Digital SMEs to simplify workflows that rely on heavy validation, opaque pipelines, or long requirements loops


* Helping shape early decisions (e.g., data sources, approach selection, automation vs.

process change) so work can move forward with confidence


* Turning valuable one-off efforts into stable, supportable processes that others can pick up and run with


* Flexing focus over time as priorities shift between discovery, execution, and enablement

Validating & Driving Adoption of AI-Assisted Work:



* Reviewing and validating AI-assisted outputs for correctness, anomalies, and assumptions before broader adoption


* Partnering with stakeholders to translate AI capabilities into workflows that meaningfully improve how work is done-not just automate a single step


* Improving trust, clarity, and reuse so AI-assisted outputs are easier to support, explain, and sustain

Challenge, Decision Framing & Escalation:



* Identifying platform, tooling, or policy constraints that limit progress
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