Senior Data Engineer

About Syngenta

At Syngenta Seeds Field Crops,we'reshaping the future of agriculture and empowering farmers to meet the ever-growing demand for food and fuel.

We’rea global Ag Tech powerhouse, headquartered in the United States, with passionate, local experts collaborating with farmers to deliver solutions that create market opportunities.

We unite precision breeding, advanced biotechnology trait choice, and digital platforms for unmatched in-field performance.

Our seeds help mitigate risks such as disease,insect,weed, and extreme weather pressures, all while promoting sustainable farming practices that protect and enhance our planet. Join our mission of revolutionizing food security and transforming agriculture.

At Syngenta, our goal is to build the most collaborative and trustworthy team in agriculture, providing top-quality seeds and innovative crop protection solutions that improve farmers' success. To support this mission, Syngenta’sAnalytics & Data Sciences teamis seeking aSenior Data Engineer in Durham, NC.

Be a member of an innovative team working in a collaborative Data Ops environment assembled from data engineers, data scientists, visualization, and analytics experts drawn from IT and R&D teams. Relationship building, collaboration, and influencing will be key in an environment of data complexity and difficult data integration challenges.

• Support an analytical data infrastructure providing application, tool and ad-hoc access to large datasets consisting of complex data types such as genomic, phenotypic, environmental, image and geospatial data.
• Lead, coach and develop more junior engineers and IT professionals.
• Engage with business stakeholders to understand strategic roadmaps and build a technical strategy to support them.
• Interface with Dev Ops teams to extract, load and transform data from a wide variety of data sources using big data technologies in AWS cloud such as Glue, EMR, and Lambda.
• Deploy high value, high performance datasets in Snowflake, such asdata warehouse design, performance tuning, and governance.
• Create and supportof real-time data pipelines built on AWS technologies such as Glue, S3, Lambda, EMR, Event Bridge, Athena, Kinesis, and IoT Core.
• Embed quality and intelligent reporting capabilities into data pipelines such as detection of anomalies and changes in trends with meaningful alerts and statistics.
• Ensure data governance, security, and cost optimization across cloud data platforms.
• Continual research onthe latest big data and visualization technologies to provide new capabilities and increase efficiency.
• Collaborate with data scientists and other tech teams to implement advanced analytics algorithms into our data pipelines that exploit our rich datasets for statistical analysis, prediction, and clustering.
• Help continually improve automation and simplify data as a service.

PLEASE NOTE: Candidates must reside in and be permanently authorized to work in the United States without current or future employer sponsorship. This encompasses, but is not limited to, OPT, CPT, and H-1B visa holders.

• Degree in computer science, information science, engineering, mathematics, or a related technical discipline.
• 8+ years of industry experience in software development, data engineering, business intelligence, data science, or a related field, with a track record of manipulating, processing, and extracting value from large datasets.
• Strong proficiency in SQL and Python.
• Strong experience with data integration (ETL/ELT) concepts and data modeling.
• Experience building and operating highly available, distributed systems of data extraction, ingestion, and processing of large datasets.
• Deep knowledge of Snowflake, encompasses data warehouse design, performance tuning, and governance.
• Experience with AWS services encompasses S3, Glue, Lambda, and EMR.
• Experience with CI/CD pipelines, infrastructure-as-code (e.g., Terraform, Cloud Formation), and Dev Ops practices.
• Able to write, debug, unit test, and performance test data integration processes.
• Able to clearly define data quality issues and implement data governance practices.
• Strong problem solving/critical thinking skills.
• Ability…