This position is not eligible for sponsorship.
Employment eligibility is limited to individuals who are authorized to work in the United States on a PERMANENT, UNRESTRICTED BASIS. This position does not support any form of visa sponsorship or work authorization, now or in the future.
LDC is seeking a talented Data Engineer to join our expanding team of Data Analytics and AI. In this role, you'll architect and implement innovative data solutions that directly impact business decision-making and operational efficiency.
As a data engineer at LDC, you'll work at the forefront of agricultural technology, building scalable data pipelines and AI-powered analytics solutions. You'll collaborate with diverse datasets—from satellite imagery and weather forecasts to market data and proprietary trading information—transforming raw data into actionable intelligence that powers our business.
Duties & Responsibilities
Data Engineering & Infrastructure
- Design, build, and maintain scalable data pipelines and ETL/ELT workflows using modern cloud-native architectures
- Design and implement robust software solutions in Python, focusing on scalability, performance, and reliability.
- Schedule and automate workflows, enhancing operational efficiency and accuracy.
- Collaborate in the development and maintenance of cloud-based infrastructure, applying best practices in DevOps to ensure high data availability and scalability.
- Work closely with data scientists, quantitative researchers, and trading teams to understand their data needs, providing technical solutions that enable effective data analysis and strategy implementation.
- Ensure code quality and maintainability by implementing strong CI/CD practices, code versioning, automated tests, and conducting thorough peer-reviews.
- Stay current with emerging trends and advancements in software development, data engineering, and cloud technologies, integrating new tools and techniques where beneficial.
- Expertise in handling and optimizing relational databases to support analytical applications
- Ensure data quality, governance, and compliance through automated testing and monitoring frameworks
Data Transformation & Modeling
- Design and implement dimensional data models, star schemas, and semantic layers optimized for analytics and reporting
- Create and maintain data models and data transformation logic using SQL and Python
- Develop automated, high-quality indicators and KPIs from diverse data sources
- Perform exploratory data analysis to uncover patterns and support business intelligence initiatives
- Collaborate with data scientists to productionize machine learning models and AI solutions