Job Description

Company Description

Syngenta is a leading agrochemicals company, dedicated to bringing plant potential to life. Each of our 30,000 employees in more than 100 countries work together to solve one of humanity\xe2\x80\x99s most pressing challenges: growing more food with fewer resources. A diverse workforce and an inclusive workplace environment are enablers of our ambition to be the most collaborative and trusted team in agriculture.

Our employees reflect the diversity of our customers, the markets where we operate and the communities which we serve. No matter what your position, you will have a vital role in safely feeding the world and taking care of our planet. Join us now and help shape the future of agriculture.



In Crop Protection R&D, we design and evolve cutting-edge data capabilities to allow us to access, connect, share and harness our R&D data at an unprecedented scale and pace. We cover a wide spectrum of data from Research (chemistry and biology research data) to open field IoT (environmental sensors, drones), NLP and image analysis. We believe in FAIR, shared and connected data products, empowered and data-savvy people, agile delivery and open source.

We are looking for an experienced lead data engineer/data architect with outstanding technical and interpersonal skills, interfacing between IT, data engineers and R&D teams. The right person is expected to play a key role in CR R&D-wide data transformation and innovation efforts by designing and building streamlined data pipelines to deliver valuable and robust data products for analytics and fulfil the strategic data needs of R&D.

Key accountabilities and expectations

• Lead data engineering matrix teams from data ingestion (structured and unstructured) to delivery of data products to drive project and business decisions
• Set guardrails and data engineering standards and documented best practices (e.g. in code development, data product specs, testing, operationalisation)
• Work in close collaboration with R&D domain data experts and with R&D IT to understand the usage requirements, profile data and assess data quality, lineage, maturity and complexity
• Design and implement prototype and production-grade data ETL/ELT pipelines. Provide integrated datasets / data products for further exploration and use
• Produce conceptual, logical, and physical data models to build fit for purpose data products using suitable (e.g. Data Mesh/Data Fabric/Lakehouse) architectures on modern data platforms.
• Understand and document data landscape, data flows, data architecture and data models (current and future ones) in CP R&D systems in collaboration with IT enterprise and solution architects
• Participate and lead CR R&D-wide data transformation efforts, such as the creation and management of data mesh architecture, data marketplace/catalogue, a shared data platform, etc.

Qualifications

• MSc in STEM or data-related sciences and engineering
• Excellent knowledge of data architecture and modelling principles and paradigms, such as modern database systems (graph and relational), data flows, data lakes, data mesh/fabric, data lakehouse, etc.
• Deep knowledge of technologies for data mining and data engineering (e.g. (No-)SQL, Python/R, Spark, Kafka, Hive, Elastic)
• Deep technical understanding working with prem and cloud environments and technologies, such as HPC clusters, Databricks and AWS and current data engineering toolkits
• Deep technical understanding of R&D concepts and how scientific data is produced and harnessed.
• Proven knowledge of scrum, agile, DevOps/DataOps and product management principles and methodology

Desired skills and experience

• PhD in STEM or a data management area
• Advanced technical knowledge of data management principles and platforms including data quality, data governance, data catalogue, master and reference data and their application in scientific R&D
• Working experience with complex scientific data and informatics flows and tools, such as omics, chemo- and/or bio-informatics
• Deep understanding and knowledge of FAIR data management concepts, such as relevant public domain scientific dictionaries, standards and ontologies (e.g. ISO, SEND, NCBI, BAO, etc.) and their application for interoperability and reusability of data
• Applied knowledge of business analysis and data architecture techniques and tools, such as data flow and process modelling, knowledge graphs, semantic integration, document mining and annotation, etc.

Essential personal capabilities

• Capacity to explain complex information and data as simple comprehensible messages.
• Experience as a lead data engineer preferably in a multinational science-based company (e.g. chemical, pharma) dealing with complex scientific data and data flows.
• Superb matrix-team leadership, technical mentorship and communication skills.
• Highly organised and structured in planning and execution of responsibilities.
• Ability to work and set goals independently and in a team to implement effective and efficient solutions.
• Ability to build networks across teams, regions, cultures and countries.

Additional Information

In return for your skills and knowledge, Syngenta will offer:

• Competitive benefits package including opportunities for flexible working.
• Up to 31.5 days annual holiday.
• Interaction with external professionals and opportunities to represent Syngenta in external networks, collaborations and conferences.
• Great onsite facilities including a staff restaurant, cafeteria, a gym and fitness classes.
• Hybrid or remote working arrangements
• Great opportunities for personal and career development.
• A modern, stimulating and dynamic working environment which promotes diversity and inclusion, scientific excellence and collaboration.
• A job and responsibilities with a purpose at state-of-the-art facilities within a world-class R&D campus site.

We embrace and encourage diversity, and this is what drives our innovation and lets us outperform the market.

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Syngenta