Our client is a U.S.-based company that provides technical expertise, testing, and certification services to the global food and agricultural industry. Their mission is to ensure food safety, quality, and sustainability across international supply chains.

This role is critical to building, maintaining, and modernizing data pipelines that process large-scale regulatory data from around the world and transform it into usable datasets for downstream applications and APIs.

The engineer will work hands-on with Python, SQL, and related tools to untangle legacy “spaghetti code” pipelines, migrate processes to more maintainable platforms such as Airflow, and ensure that our data is accurate, reliable, and ready for client-facing products. This role requires both strong technical ability and a consulting mindset—able to learn undocumented systems, troubleshoot gaps, and design forward-looking solutions that will scale as our data environment evolves.

Required Qualifications:

• Minimum 7 years’ experience using Python for analyzing, extracting, creating, and transforming large datasets.
• Proficiency in Python 3+ and common Python libraries and tools for data engineering, specifically Pandas, NumPy, and Jupyter Notebooks.
• Deep experience with SQL and relational data using Oracle, Postgres, or MS SQL Server.
• Solid understanding of database design principles, data modeling, and data warehousing concepts.
• Excellent troubleshooting skills and instincts.
• Curious, self-motivated, and self-directed; comfortable working within an Agile software development team with short, iterative delivery cycles.
• College degree or equivalent experience in computer science, software development, engineering, information systems, math, food science, or other applicable field of study.

Preferred Qualifications:

• NoSQL database design and development using MongoDB, AWS DynamoDB, or Azure Cosmos DB.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and services related to data storage/processing
• Exposure to Terraform or other Infrastructure-as-Code tooling.
• Proficient in Azure DevOps for source code and pipeline management.