Data Engineer : Advanced Engineer

Brady makes products that make the world a safer and smarter place. We are a global leader in safety, identification and compliance solutions for a diverse range of workplaces. From the depths of the ocean to outer space, from the factory floor to the delivery room — we’re just about everywhere you look.

Companies around the globe trust Brady because of our deep expertise and knowledge across a wide range of industries and applications, powered by our world-class manufacturing capabilities.

We have a diverse customer base in industries including electronics, telecommunications, manufacturing, electrical, construction, healthcare, aerospace and more. As of July 31, 2023, Brady employed approximately 5,600 people worldwide. Our fiscal 2023 sales were approximately $1.33 billion. Brady stock trades on the New York Stock Exchange under the symbol BRC. You can learn more about us at www.bradycorp.com.

Key Responsibilities

• Architect and develop end‑to‑end data pipelines on Azure using Databricks (Spark / PySpark)
• Design and maintain lakehouse architectures using Azure Data Lake + Delta Lake
• Build and optimize batch and streaming pipelines for large‑scale datasets
• Create and manage feature pipelines and curated datasets for AI/ML model training and inference
• Collaborate with data scientists and ML engineers to enable scalable ML workflows
• Support MLOps pipelines, including data versioning, feature stores, and model deployment readiness
• Optimize Databricks workloads for performance, scalability, and cost efficiency
• Implement data quality, validation, monitoring, and observability frameworks
• Ensure data security, governance, and compliance using Azure and Databricks best practices
• Review code, define standards, and mentor junior and mid‑level data engineers
• Lead architectural decisions and contribute to data platform roadmap planning

Required Skills & Qualifications

• 6+ years of hands‑on experience in Data Engineering or Data Platform roles
• Strong proficiency in Python, PySpark, and Spark SQL
• Extensive experience with Databricks (jobs, notebooks, workflows, Delta Live Tables)
• Strong experience with Azure Cloud services, including:
  • Azure Data Lake Storage (ADLS Gen2)
  • Azure Databricks
  • Azure Data Factory / Synapse Pipelines
• Solid understanding of Delta Lake, including optimization and ACID guarantees
• Advanced SQL skills for analytical data modeling
• Experience designing AI/ML data pipelines (training, validation, inference datasets)
• Knowledge of data warehousing, lakehouse, and dimensional modeling concepts
• Familiarity with CI/CD, Git, and DevOps practices
• Strong troubleshooting, performance tuning, and problem‑solving skills

Preferred / Nice‑to‑Have Skills

• Experience with ML platforms such as Azure Machine Learning or Databricks ML
• Hands‑on experience with Feature Store, MLflow, or experiment tracking
• Streaming data experience (Kafka, Event Hubs, Spark Structured Streaming)
• Experience with dbt, Unity Catalog, or data governance tools
• Knowledge of BI and visualization tools (Power BI preferred)
• Exposure to MLOps best practices and production ML systems
• Prior experience as a technical lead or mentor

All your information will be kept confidential according to EEO guidelines.