
Building Large-Scale Data Pipelines Specialist
4 semanas atrás
This role requires a skilled professional to build, maintain and modernize data pipelines that handle large-scale regulatory information worldwide.
The engineer will work closely with Python, SQL, and related tools to clarify legacy code, migrate processes to more maintainable platforms, and ensure data precision, reliability, and readiness for client-facing products.
Key Responsibilities:
- Design, develop, test, and deploy data pipelines using Python, SQL, and associated tools.
- Migrate legacy code to more maintainable platforms such as Airflow.
- Ensure data accuracy, reliability, and readiness for client-facing products.
Requirements:
- A minimum of 7 years' experience in using Python for analyzing, extracting, creating, and transforming large datasets.
- Proficiency in Python 3+ and common Python libraries and tools for data engineering.
- Deep knowledge of SQL and relational data using Oracle, Postgres, or MS SQL Server.
- A solid understanding of database design principles, data modeling, and data warehousing concepts.
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.
- Experience with Terraform or other Infrastructure-as-Code tooling.
We are a US-based company providing technical expertise, testing, and certification services to the global food and agricultural industry. Our mission is to ensure food safety, quality, and sustainability across international supply chains.
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