Valmont impacts millions of people around the world every day, yet they might not realize the many ways. Our technology is helping feed the growing population, supplying the world with more reliable energy and access to renewables, enhancing connectivity in remote and urban locations to create a sustainable future and so much more. Simply put, Valmont is advancing agricultural productivity and reimagining vital infrastructure to make life better. The Manager, Data Products & Engineering will be a hands-on and business-savvy data leader managing the development of data products and platforms that drive strategic insights and operational efficiency.
Requirements
- Strong hands-on proficiency in SQL, Python, and Databricks.
- Design and optimize scalable data pipelines using Databricks notebooks and Delta Lake for both batch and streaming data processing.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Skilled in designing and managing data pipelines, data models, and analytics platforms.
- Familiarity with CI/CD practices, DevOps for data, and version control tools like GitHub or Azure DevOps.
- Experience with BI and visualization tools (e.g., Power BI, Tableau, Looker).
- Understanding MLOps and deploying ML models in production environments.
Responsibilities
- Lead the design and delivery of data products that support business goals and customer needs.
- Collaborate with product, business, and technology teams to translate requirements into scalable data solutions.
- Architect and manage data pipelines, data models, and analytics platforms using tools like Databricks, SQL, and Python.
- Drive the development of dashboards, ML models, and self-service analytics for business stakeholders.
- Ensure data quality, governance, and performance across systems.
- Mentor and manage a cross-functional team of data professionals.
- Design and optimize scalable data pipelines using Databricks notebooks and Delta Lake for both batch and streaming data processing.
Other
- Bachelor’s degree is preferred with 10+ years of experience, or Associate’s degree with 12+ years.
- Minimum of 10 years of experience in data engineering, analytics, or machine learning, including at least 2 years in leadership or product-focused role.
- Reports to the Director, Software & Data Engineering and will have direct reports.
- Experience with model monitoring, retraining, and performance tracking to ensure ML models remain accurate and relevant in production.
- Familiarity with ML lifecycle tools and platforms such as MLflow, SageMaker, or Azure ML for managing experiments, deployments, and versioning.
