Data Engineer

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 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 delivering and supporting 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 Engineer 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 1-3 source systems.     Key Responsibilities   1. Execute

Collaborate with data product managers to gather data requirement

Execute ETL solutions including data security, data quality and performance requirements.

Prepare documentation of data product lineage and all other related ETL topics.

2. Data Extraction, Load and Transformation

Implement and maintain 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. Support the development and maintenance of 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.

3. Process Improvement, Performance and Cost optimization tuning

Collaborate with Data Science, AI, and Data product teams to optimize performance and cost effectiveness of their solutions.  Identify and support the design of internal process improvements, including automating manual processes, optimizing data product delivery, and redesigning solutions for enhanced scalability.  Implement solution adjustments to improve performance and cost-effectiveness of data products.

4. Issue Resolution and Support

Assist stakeholders with data-related product pipeline issues and support their data product needs.  Work with the Analytics Operational Support team to investigate, troubleshoot, and resolve data errors / discrepancies.

Required Qualifications:    Level of Education and Discipline

Bachelor’s degree in Mathematics,