Senior Data Engineering Manager - T&T

At McCormick, we bring our passion for flavor to work each day. We encourage growth, respect everyone's contributions and do what's right for our business, our people, our communities and our planet. Join us on our quest to make every meal and moment better.

 

Founded in Baltimore, MD in 1889 in a room and a cellar by 25-year-old Willoughby McCormick with three employees, McCormick is a global leader in flavour. With over 14,000 employees around the world and more than $6 Billion in annual sales, the Company manufactures, markets, and distributes spices, seasoning mixes, condiments and other flavourful products to the entire food industry, retail outlets, food manufactures, food service businesses and consumers.

 

While our global headquarters are in the Baltimore, Maryland, USA area, McCormick operates and serves customers from nearly 60 locations in 25 countries and 170 markets in Asia-Pacific, China, Europe, Middle East and Africa, and the Americas, including North, South and Central America

 

 

Position Overview

 

As a Data Engineer at McCormick, you will play a pivotal role in delivering the design, implementation and maintenance of data and analytics solutions from simple to complex and supporting McCormick AI engineers with their data needs. Your responsibilities will include implementing and maintaining data solutions delivering data required by McCormick AI solutions.  You will work with Data Scientists and AI Engineers to convert business expectations into data solutions and data models used to deliver AI-driven recommendations to stakeholders and executives.

 

Key Responsibilities:

 

• Design and implement scalable ELT pipelines on an Azure analytics platform to ingest, harmonize and transform data into data models optimized for AI consumption.
• Write efficient and scalable code to transform and clean large volumes of data.
• Ensure performance, security and data integrity across end-to-end data processing.  
• Cooperate with cross-functional teams to design and deliver new data solutions and improve and enrich existing ones.

 

The role will report to the Azure Analytics Product Owner and requires close collaboration with the entire Enterprise Data Services team and McCormick AI team to conceptualize, visualize, and build an enterprise data management framework

 

Requirements:

• Proven experience with Azure Databricks.
• Proven experience with ML/AI tools.
• Proven experience with Azure Analytics toolset (Data Factory, Synapse, Storage Accounts, Key Vault)
• Proficiency with T-SQL, Python, PySpark
• Performance tuning experience within the Azure analytics environment: parquet/delta files, SQL databases, data warehouses, ingestion tuning, cache optimization, etc.
• Good communication skills including ability to interact closely with Data Science and AI Engineers.
• Experience with Agile methodologies (Azure DevOps).
• Experience with CI/CD tools (Azure DevOps, Git)

 

Desired Experience:

• Experience with Microsoft Fabric
• Familiar with SAP, SAP BW or any other ERP system
• Familiar with Data Governance / MS Purview
• Experience with Power BI

 

Decription

 

1. Plan and Design

• Collaborate with business stakeholders to gather requirements.
• Design end-to-end solutions including data security, data quality and performance requirements.
• Prepare documentation and with Product Owner define implementation plan

     2.Data Extraction, Load and Transformation

• Implement data pipelines to efficiently prepare data for ML/AI needs and deliver datasets that meet Data Science and AI Engineers requirements.
• Ensure efficient and reliable data mapping to support business needs.
• Deliver complete documentation and knowledge transfer sessions for the Team and partners
• Maintain existing solutions, implement optimizations and enhancements, monitor data quality  

     3.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 and impl