Data Modeler

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Skills you'll use

What you'll do

• Own, maintain, and improve production data pipelines across the Coffee Platform.
• Build and maintain ingestion pipelines for internal data sources, including business-generated Excel/CSV files, reports, and other internal datasets.
• Maintain integrations with external data sources, including exchanges, APIs, web-scraped data, and weather providers.
• Proactively monitor pipeline execution, investigate failures, perform root-cause analysis, and implement corrective actions.
• Own pipeline health and observability reporting through platform centralized monitoring, including data freshness, failures, ownership, dependencies, and data quality.
• Design and maintain robust database structures, SQL workflows, schemas, indexes, and data models.
• Maintain orchestration and scheduling of production workflows with appropriate logging and alerting.
• Support data scientists and researchers with reliable, production-ready datasets and pipelines.
• Maintain clear data lineage and documentation and contribute to overall data governance standards.
• Support database administration and production incident investigation where required.

Who can apply

• 3+ years of professional Data Engineering experience.
• Strong Python development skills, particularly for ETL/data pipelines, APIs, data processing, automation, and production workflows.
• Strong SQL skills, including database/data-model design and optimization.
• Experience with workflow orchestration and scheduling tools such as Jenkins, Airflow, Azure Data Factory, or equivalent.
• Experience implementing pipeline monitoring, logging, alerting, and data-quality controls.
• Strong experience with Git-based version control and collaborative development workflows, including branching, pull requests, and code reviews.
• Additional Information
• Databricks experience.
• MongoDB / NoSQL experience, particularly MongoDB Atlas.
• MongoDB administration and operational troubleshooting experience, including the ability to interpret Atlas/database logs, investigate incidents, understand database operations, and identify root causes of unexpected data changes or failures.

Perks & benefits

About Louis Dreyfus Company

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