Data Engineer developing data pipelines at Corteva Agriscience for analytics and reporting. Collaborating with cross-functional teams to support data-driven decision-making in agriculture.
Responsibilities
Design, build, and maintain scalable data pipelines and ETL processes to support analytics, reporting, and data science initiatives
Develop and automate robust workflows for data ingestion, transformation, and delivery using orchestration tools and CI/CD pipelines
Leverage cloud platforms (Azure preferred) and technologies (Databricks, Azure Data Factory) to manage big data environments and enable advanced analytics
Participate in code reviews (PRs), enforce coding standards, and collaborate with cross-functional teams to ensure maintainable, high-quality solutions
Implement monitoring and observability for data pipelines, proactively identifying and resolving issues in production environments
Ensure data integrity, security, and compliance by applying best practices in data governance, quality management, and documentation
Work closely with business partners to understand requirements, deliver custom data solutions, and provide training and support for end users
Requirements
Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field (Master’s preferred)
2-3 years of relevant experience, or a Master’s degree in a related field
Strong proficiency with SQL, Python, and PySpark for data engineering tasks
Hands-on experience with cloud computing technologies for big data (Azure preferred), including Databricks and Azure Data Factory
Experience building and maintaining production-grade data pipelines, including monitoring and troubleshooting in live environments
Proficiency in using Git for version control and collaboration; experience participating in code reviews (PRs) and enforcing code quality standards
Experience working in an Agile environment, with knowledge of Agile methodologies and practices
Hands-on experience with CI/CD pipelines for automating data pipeline deployment and testing
Deep understanding and experience with Azure’s cloud architecture, services, and management tools
Knowledge of MLOps best practices, including deployment, monitoring, and maintenance of machine learning models
Experience participating in code reviews and collaborative development processes
Experience with building automated pipelines for data workflow deployment and monitoring in Azure Databricks
Experience supporting data-driven business transformation and data governance initiatives
Benefits
Numerous development opportunities offered to build your skills
Be part of a company with a higher purpose and contribute to making the world a better place
Health benefits for you and your family on your first day of employment
Four weeks of paid time off and two weeks of well-being pay per year, plus paid holidays
Excellent parental leave which includes a minimum of 16 weeks for mother and father
Future planning with our competitive retirement savings plan and tuition reimbursement program
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