DataOps Engineering Manager

Louisiana-Pacific Corporation (LP Building Solutions) is a leading provider of high-performance building solutions that meet the demands of builders, remodelers, and homeowners worldwide. We manufacture engineered wood building products that include an extensive offering of innovative and dependable building materials and accessories. LP’s values-driven culture creates an environment where talented and hardworking people thrive in an ethical, inclusive, challenging, and rewarding place to work. Since our founding in 1972, we’ve developed careers and provided advancement opportunities in the building products industry. Headquartered in Nashville, Tennessee, LP operates more than 20 facilities across North and South America. For more information, visit LPCorp.com.

Job Purpose

The DataOps Engineering Manager will play a crucial role in developing, shaping, and executing our data engineering strategy. This IT leader is responsible for leading a team of technology professionals focused on data engineering, data science, and architecture to build and maintain robust data infrastructure, ensuring data quality, and enabling data-driven decision-making across the organization. The ideal candidate will leverage their expertise in data engineering and DataOps methodologies to streamline data workflows, enhance the availability and accessibility of data assets, and drive continuous improvement. This role is pivotal in transforming raw data (structured & unstructured) into actionable insights that support our business’ analytical needs and accelerate the identification of key business insights. 

In this position you will have the opportunity to:

• Lead and mentor a team of data engineering professionals, providing guidance and support to ensure the successful delivery of data projects.
• Design, develop, and maintain scalable data pipelines and ETL processes to support data integration and analytics.  Occasional hands-on activity with these process, as needed.
• Join forces with cross-functional teams, including business analysts, functional and technical architects, and key business stakeholders, to understand data requirements and deliver solutions that meet their needs.
• Collaborate with business and technology leaders to develop and execute the AI and Technical Innovation strategy to identify, trial, implement, and scale LP’s investments in emerging technologies.
• Ensure data quality and integrity by implementing best practices for data governance, data validation, and data observability.
• Identify & solution opportunities for optimization, process enhancements, and new technologies and tools to enhance operational reliability of data management processes.
• Optimize data storage and retrieval processes to improve performance and efficiency.
• Implement and promote DataOps methodologies to streamline data workflows, improve collaboration, and enhance the overall efficiency of data operations and the delivery of data products.
• Manage and prioritize multiple projects and initiatives utilizing a blend of agile and waterfall methods, ensuring timely delivery of data products and alignment with business goals.
• Develop and maintain automated testing, monitoring, and deployment processes to ensure the reliability and scalability of data solutions.
• Foster a culture of continuous improvement by encouraging the adoption of CI/CD processes to optimize and improve workflows.
• Builds successful stakeholder relationships with other IT and business stakeholders by developing a clear understanding of business outcomes, acting as a trusted internal advisor, and ensuring cost-effective design & delivery of data services and products to meet those needs.
• Assesses emerging data engineering technologies for applicability to business objectives, leading proof-of-concept projects, identifying design opportunities for automation, and making recommendations for continuous improvement
• Operates within the formal data governance framework to establish and monitor effective controls for all data assets and the processes and functions performed by the Data Engineering team, including policies and standards for data cataloging, lineage, quality, and process orchestration.
• Supports periodic reviews by audit, compliance and other risk-related functions, as required.
• Support Enterprise Architecture team by reviewing and contributing to architectural blueprints, roadmaps, and documentation to support development and integration efforts.  Recommend changes, as required.
• Develop and execute the data strategy across technology platforms for LP’s data assets, including oversight of data engineering & integration activities.
• Other duties as