Senior Data Engineering Manager - T&T

You may know McCormick as a leader in herbs, spices, seasonings, and condiments – and we’re only getting started. At McCormick, we’re always looking for new people to bring their unique flavor to our team. McCormick employees – all 14,000 of us across the world – are what makes this company a great place to work. Position Summary: As a Data Engineering Manager at McCormick, you will play a pivotal role in the build and delivery of data products from simple to complex and supporting McCormick business units with their data and analytics needs. Your responsibilities will include leading a team that delivers and supports data for existing analytics solutions, tooling, and solutions, researching new features and implementing automations. You will support business users, Data Scientists and Data Analysts to convert business expectations into data products and data models usable by business to deliver AI, analysis, reporting, and data-driven recommendations to stakeholders and executives. This role will be accountable for building and maintaining scalable data pipelines from source systems. The Data Engineering Manager will ensure the availability, reliability, and performance of data products by integrating raw data from various sources. Key responsibilities include data modeling, ETL (Extract, Transform, Load) development, and ensuring data quality and security. This role will be accountable for data coming in from 5+ source systems. Key Responsibilities: Plan and Design • Collaborate with data product managers to gather data product requirements. • Design end-to-end solutions including data security, data quality and performance requirements. • Prepare documentation and with data product managers to define the implementation plan. Data Extraction, Load and Transformation • Implement ELT pipelines to efficiently ingest and transform data from a wide variety of data sources and deliver datasets that meet business requirements. • Ensure efficient and reliable data mapping to support business needs. • Deliver complete documentation and knowledge transfer sessions for the Team and business partners. • Maintain existing solutions, implement optimizations and enhancements, monitor data quality. • Develop and maintain scalable data pipelines leveraging Azure Synapse, PySpark, APIs, and SQL & performing advanced data cleaning, transformation, and manipulation to ensure high-quality, and reliable data flows. Process Improvement, Performance and Cost optimization tuning • Collaborate with Data Science, Machine Learning and Business Analytics teams to optimize performance and cost effectiveness of their analytics solutions. • Identify and design internal process improvements, including automating manual processes, optimizing data delivery, and redesigning solutions for enhanced scalability. Work with Azure Analytics Product Owner to prioritize and schedule implementation. • Design…