The Data Sciences Software Engineer is responsible for designing, building, and maintaining modern data infrastructure and analytical solutions to support business intelligence, precision agriculture, predictive modeling, and decision support systems. This role is critical in enabling data-driven insights by developing a scalable Data Lakehouse, implementing data integration pipelines, and leveraging advanced analytics and machine learning techniques to optimize agricultural operations and business performance.
Requirements
- Proficiency with ANSI SQL and NoSQL databases, Python/ R / C++ and data modeling techniques.
- Experience with cloud platforms (AWS, Azure, GCP) and data lakehouse technologies (Delta Lake, Snowflake, Databricks etc.).
- Knowledge of ETL tools and orchestration frameworks and proficiency in API integration.
- Understanding of data governance, security, and compliance.
- Experience with agriculture technology, geospatial data, or IoT telemetry.
- Familiarity with machine learning workflows, MLOps, and AI-based decision systems.
- Experience deploying solutions in containerized environments (Docker, Kubernetes).
Responsibilities
- Design, develop, and implement a scalable Data Lakehouse environment to integrate structured, semi-structured, and unstructured data sources, including IoT, satellite imagery, weather data, and field telemetry.
- Implement robust ETL/ELT processes to collect, transform, and load data from diverse internal and external sources into the Lakehouse environment.
- Integrate data from agricultural equipment, ERP systems, cloud platforms, and third-party APIs.
- Select and configure appropriate ETL tools and platforms (e.g., Apache Airflow, Talend, dbt, AWS Glue) to support repeatable, scalable workflows.
- Deploy and manage data analytics and visualization platforms (e.g., Power BI, Tableau, Looker, KNIME) and support cross-functional teams in generating actionable insights.
- Work closely with key technology stakeholders to enable advanced analytics, predictive modeling, and machine learning workflows.
- Optimize query performance and resource usage for large-scale datasets.
Other
- Adherence to safety policies.
- Promoting and adhering to the company Core Values of honesty, integrity & teamwork.
- Promptly and regularly report to work and work overtime hours as needed.
- Works with other cooperative staff at other locations to ensure cooperative goals are met.
- Present a clean and professional appearance.
