[Hiring] Senior Data Analyst @Stanley Black & Decker, Inc.

Role Description

As a Sr. Data Analyst, you’ll be part of our Tools and Outdoor Analytics team you’ll get to:

• Collect, analyze, transform, and consolidate large volumes of data, working with internal team as well as business unit stakeholders including verifying and validating data accuracy to ensure integrity.
• Design, develop, and maintain ETL/ELT data pipelines using SQL, Python, and distributed processing frameworks.
• Build and optimize data solutions on Snowflake, ensuring performance, reliability, and scalability.
• Develop and maintain PySpark/Snowpark data transformations for large-scale data processing.
• Support MLOps workflows, including model deployment, automation, monitoring, and reproducibility.
• Collaborate with data scientists to prepare high-quality datasets for modeling and analytical use cases.
• Use GitHub for version control, CI/CD automation, and code review best practices.
• Develop and prototype data workflows in Jupyter Lab, ensuring reproducible and well-documented analysis.
• Partner with IT, product, and business stakeholders to translate requirements into technical solutions.
• Troubleshoot complex data issues, ensuring data quality, accuracy, and availability across systems.
• Self-starter that can manage a project effectively with a high level of self-confidence.
• Ability to manage multiple assignments with competing deadlines.
• Ability to work independently and remotely, troubleshoot problems with minimal oversight.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 3 years data analytics or business analytics experience.
• Strong proficiency in SQL, including complex joins, CTEs, window functions, and performance tuning.
• Hands-on experience working with Snowflake (warehousing, Snowpark, task orchestration, query optimization).
• Proficiency in Python, especially within data processing, automation, and analytical workflows.
• Experience with PySpark or Snowpark for large-scale distributed data processing.
• Understanding of MLOps principles (model lifecycle, automation, CI/CD, monitoring).
• Experience using GitHub for version control, pull requests, branching strategies, and workflow automation.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity working in Jupyter Lab for prototyping and exploratory data development.

Benefits

• Competitive salary and a great benefits plan.
• Be part of our global company with 20+ brands to grow and develop your skills along multiple career paths.
• Access to a wealth of learning resources, including our digital learning portal.
• Experience an awesome place to work, where we have mutual respect and a great appreciation for a wide range of perspectives and experiences.
• Help us continue to make positive changes locally and globally through volunteerism, giving back, and sustainable business practices.