Data Engineer

Carlisle Construction Materials LLC (CCM) is a diversified manufacturer and supplier of premium building products and related technologies for the commercial and residential construction markets. Carlisle is one of the most respected companies in the building materials industry. After being around for more than 100 years, our customers know us for our superior products, remarkable service, and groundbreaking innovations. Our culture at CCM is one that values collaboration and team success over individual credit. Carlisle core values are safety, bias for action and results, continuous improvement, teamwork and communication, customer focus, empowerment, and mutual trust respect, and integrity. These core values are the center of all business decisions and make CCM the successful company that it is.

Job Summary

The Data Engineer will be responsible for delivery of innovation acceleration and R&D service improvement through the design, implementation, and maintenance of company data. The data engineer will play a key role in the digitalization of the research and innovation team. The data engineer will be responsible for creating and maintaining data sets and predictive models that help the organization make informed business decisions. The role involves full-stack development and consulting to maximize insights from large and diverse data sources. This will be a high visibility role reporting to the manager of data science and operating under the general guidance of the CCM EVP R&D and the Director of Innovation.

Duties and Responsibilities:

• Partner with the Innovation Director, R&D scientists, and management team members to identify opportunities for the application of data science to accelerate product and service innovation and improve R&D service to the business.
• Execution, delivery, and communication of data projects that will help turn disparate data points into data informed action and accelerate innovation and R&D services.
• Identify, harness, clean, and analyze large amounts of related data and implement models to provide access for data visualization and applications. Implement and maintain data pipelines to enable real-time data processing.
• Work closely with data others to ensure data security, reliability, quality, consistency, and completeness.
• Develop and implement statistical models, machine learning algorithms, and predictive models to identify patterns and insights from data.
• Mentor and collaborate with R&D scientists, directors, and managers to identify projects and ensure proper use of data in innovation and support research resulting in the creation of business value and a culture of data-driven innovation.
• Establish and continuously improve data science architecture, technology stack, standards, and processes to improve data architecture and data solutions.
• Advocate and promote data informed innovation within CCM through visualization, presentations, and project communication.
• Stay current with emerging trends and technologies in data science, machine learning, and artificial intelligence.

Required Skills/Abilities/Knowledge:

• Demonstrated strong agile project management capabilities (certifications appreciated).
• Strong business acumen and ability to illustrate and communicate business value for data projects.
• Expertise in data modeling, data quality checks, and optimization of existing pipelines.
• Understanding and experience working with cloud infrastructure services like Microsoft Azure.
• Experience with web application development, data API integration, data analytics, AI, big data platforms, and automating machine learning components.
• Experience in any database technology (e.g., SQL Server/Azure Cosmos DB/Amazon Athena)
• Working knowledge of software, and hardware commonly utilized in a data science environment:
  • Knowledge of data science languages and toolkits (such as R, Python, Java, NumPy, and MatLab)
  • Experience with big data analytics technologies (such as Spark and Hadoop)
  • Experience with data visualization tools (such as D3.js and Tableau)
  • Experience working with different query languages
  • Expertise in data mining, collection, and machine learning
  • Ability to store and process unstructured data with databases and machine learning models
• Outstanding verbal and written communication skills, with the ability to translate technical details in business language and relate technical concepts to a business impact.
• Advanced analytical and root cause problem-solving skills.
• A demonstrated ability to leverage existing resources to maximize technology investments.