Senior Data Engineer

Syngenta Group•Durham, NC

16h•$114,100 - $163,000•Hybrid

About The Position

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’s Analytics & Data Sciences team is seeking a Senior Data Engineer in Durham, NC. Be a member of an innovative team working in a collaborative DataOps 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.

Requirements

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, CloudFormation), and DevOps 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 to lead, mentor and coach other engineers.
Ability to communicate with, and influence, senior stakeholders.
Desire to work with Agile/DataOps practices and methodologies.

Responsibilities

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 DevOps 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 as data warehouse design, performance tuning, and governance.
Create and support of real-time data pipelines built on AWS technologies such as Glue, S3, Lambda, EMR, EventBridge, 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 on the 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.