Job description
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.
Accountabilities:
Build, test, and maintain robust, scalable, secure, highly available data pipelines and reservoirs that store, clean, transform, and aggregate streaming data.
Partner closely with architects and the security team; understand the holistic view of edge computing, security and data strategy; drive streaming data ingestion from gateway to storage - all in the agriculture realm.
Expose data as consumable data sources for analytics via APIs and data virtualization services such as Denodo.
Well versed in cloud services such as AWS, Kinesis, Glue, Redshift/Spectrum, S3, Lambda, EMR, EventBridge, Lake Formation, and Athena.
Continual research of the latest streaming data services and technologies to provide new capabilities and increase efficiency.
Collaborate with data scientists and other tech teams to implement advanced analytics that exploit our rich datasets for statistical analysis, prediction, clustering, and machine learning.
Help continually improve automation and simplifying data as a service.
Qualifications:
- Degree in computer science, information science, engineering, mathematics or related technical discipline.
- 3+ years of industry experience in software development, data engineering, business intelligence, data science, or related field with a track record of securing, manipulating, processing, and extracting value from large datasets.
- Strong experience with data integration (ETL/ELT) concepts.
- Cloud experience, preferably AWS
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Knowledge of, and experience with data transformation technologies and tools
- Experience with SQL and NoSQL technologies
- Desire to work with Agile/DataOps practices and methodologies in a highly collaborative environment
- Experience with continuous integration practices
- Able to write, debug, unit test, and performance test data integration processes
- Able to clearly define data quality issues
- Strong problem solving/critical thinking skills
Additional Knowledge, Skills, Traits & Abilities:
- Relational databases including Amazon RDS and Redshift.
- AWS technologies including S3/parquet, Glue, EMR, Lambda
- Data streaming technologies (Kinesis, Kafka) desirable
- Geospatial data manipulation and storage desirable
- Python and Java programming
- R and statistical methods
- Business rules engines such as Drools a plus
- Data virtualization such as Denodo or Tibco a plus
- Data modeling
Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status.
Family and Medical Leave Act (FMLA)
(http://www.dol.gov/whd/regs/compliance/posters/fmla.htm)
Equal Employment Opportunity Commission's (EEOC)
(http://webapps.dol.gov/elaws/firststep/poster_direct.htm)
Employee Polygraph Protection Act (EPPA)
(http://www.dol.gov/whd/regs/compliance/posters/eppa.htm)
