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# Business Intelligence Engineer

- **Company:** Brady Corporation
- **Location:** Milwaukee, WI, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, Data Analysis, Applications Architecture, Software Applications, Business Software, Cloud Database, Databases, Information Engineering, Python (Programming Language), OAuth, Software Tools, Cloud Services, Standard Sql, Software Engineering, SQL Databases, Enterprise Data Management, File Transfer Protocol (FTP), Enterprise Software Applications, Technical Debt, Backend, Solid Principles, Information Technology, Integration Frameworks, Data Delivery, Api Design, Restful APIs, Code Restructuring, Stream Analytics, Data Pipelines, Api Management
- **Published:** October 16, 2026
- **Apply:** https://www.juju.com/job/1_bradycorporation-5001230340406

## About the Role

What You Will Need To Be Successful: + Bachelor's degree in Computer Science, Software Engineering, Math, Statistics, Data Science, or a quantitative technical field. + 3-5+ years of experience in analytics engineering, data engineering, or software development building data-heavy software applications or automated data engines. + Strong proficiency in Python software design principles (modular code design, API development, backend logic structuring, and asynchronous workflow handling). + Expert-level SQL skills; experience structuring multi-layer data pipelines, engineering feature sets, and tuning query execution in cloud data warehouses. + Solid foundation in applied statistical methods (e.g., regression, clustering, segmentation) and the ability to operationalize model outputs into actionable software triggers. + Proven experience integrating third-party REST APIs, managing modern authentication flows (OAuth, Service Accounts), and orchestrating automated batch data transfers. +
Active humility, creative problem-solving skills, and strong communication skills to explain technical application design to non-technical stakeholders.

## Description

What We Need: We are seeking a driven Senior Business Intelligence Engineer for our team.
At Brady, this role functions as a hybrid Analytics Engineer and Data Application Developer, transforming analytics and enterprise data into production-grade tools.
You will bridge cloud data warehouses and functional software by building Python backend services, dynamic query engines, and automated API integrations to stream analytics, dynamic segmentation, and predictive models to business applications and external platforms.
Operating on a two-week sprint cadence, our team uses a 60/20/20 capacity model (Planned Work / Ad-Hoc / Protected Tech Debt Buffer) to safeguard your time for writing scalable code, maintaining backend services, and building data pipelines without operational overload.
What You'll Be Doing: + Data Application & Backend Engineering: Design, write, and maintain Python-based backend logic and RESTful APIs that turn data models and predictive rules into interactive software tools. + Architecture & Dynamic Query Compilation: Construct and scale the Account 360 Medallion Architecture in cloud data platforms.
Design programmatic SQL generation engines and asynchronous processing workflows to execute complex, multi-layered segmentation logic. + Third-Party Integrations & Data Delivery: Develop and maintain automated data delivery connectors using REST APIs, native SDKs, and secure file transfer protocols to keep enterprise systems and external platforms continuously synchronized. + Productionizing Analytical & Predictive Models: Work closely with statistical concepts to translate predictive models, scoring systems, and segmentation algorithms into performant, automated backend logic. + Code Refactoring & System Health: Manage your workload within our 10-point sprint capacity model, utilizing your protected 20% tech debt buffer to continuously refactor codebases, optimize database execution performance, and maintain application architecture. + Cross-Training & Collaboration: Actively participate in our cross-training framework, dedicating 4 hours per sprint to co-piloting engineering
tasks and analytical techniques with peers.