Senior Analytics Engineer: Production-Grade Data Tools

Brady Corporation; Milwaukee (WI); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Comprehensive medical/dental/vision

401(k) with company match

Paid time off and holidays

Employee Resource Groups

Education reimbursement

Job summary

Brady Corporation is seeking a Senior Business Intelligence Engineer to blend analytics engineering with data application development. The role focuses on turning analytics and enterprise data into production-grade tools, bridging cloud data warehouses with backend services, and deploying automated integrations to business applications.

You will work in sprints to design scalable data pipelines, implement dynamic query engines, and productionize predictive models, all while maintaining robust

Qualifications

• 3–5+ years of 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.

Responsibilities

• Data Application & Backend Engineering: Design, write, and maintain Python-based backend logic and RESTful APIs for interactive tools.
• Architecture & Dynamic Query Compilation: Build multi-layered segmentation logic in cloud platforms and design programmatic SQL generation engines.
• Third-Party Integrations & Data Delivery: Develop automated data delivery connectors via REST APIs, SDKs, and secure file transfer protocols.

Skills

Python

SQL

REST APIs

Data pipelines

Cloud data platforms

Education

Bachelor's degree in CS/SE/Math

Tools

Airflow

Git

Job description

Brady Corporation is seeking a Senior Business Intelligence Engineer to blend analytics engineering with data application development. The role focuses on turning analytics and enterprise data into production-grade tools, bridging cloud data warehouses with backend services, and deploying automated integrations to business applications.

You will work in sprints to design scalable data pipelines, implement dynamic query engines, and productionize predictive models, all while maintaining robust