Reporting Automation / AI Developer

BMO•Chicago, IL

5d•$75,000 - $160,000•Hybrid

About The Position

The Reporting Automation / AI Developer is responsible for designing, developing, and maintaining automated reporting solutions that improve efficiency, accuracy, and scalability across risk reporting processes. This role combines reporting automation, AI-enabled workflows, application development, and technical problem solving to modernize legacy processes and support future-state reporting platforms. You will partner closely with risk reporting teams to translate manual, fragmented processes into reliable, automated pipelines—serving as the technical bridge between raw risk data and the accurate, timely reports our stakeholders depend on.

Requirements

A few years of hands-on experience in reporting automation or data development, with a strong mastery of SQL (complex views, stored procedures, and performance tuning).
Proven ability to use Python and Shell scripting to automate reporting workflows and build supporting applications.
Familiarity applying AI-enabled workflows and tooling to modernize and accelerate reporting processes.
Version control using Git and a solid grasp of dimensional modeling and modern data warehouse concepts.
A self-starter with the technical maturity to manage deliverables and troubleshoot complex problems with minimal supervision.
Independently investigate data quality and reporting issues, identify root causes, and implement durable technical remediations.
Communicate clearly with both technical and non-technical stakeholders to ensure alignment, transparency, and data integrity across risk reporting.

Nice To Haves

Hands-on experience with Power BI (DAX / Power Query) is a plus
Familiarity with Microsoft Fabric is also a plus.

Responsibilities

Design, develop, and maintain automated reporting solutions that improve the efficiency, accuracy, and scalability of risk reporting processes.
Build and integrate AI-enabled workflows to streamline data preparation, validation, and report generation, reducing manual effort and turnaround time.
Develop and maintain applications and scripts (Python / Shell) that support reporting automation, monitor system health, and improve the reliability of risk reporting operations.
Re-engineer legacy, manual reporting processes into modern, automated pipelines that support future-state reporting platforms.
Design optimized data marts and star schemas tailored for Power BI consumption, and optimize SQL to deliver accurate risk reporting outputs.