Data Engineer at Syngenta Group

pune, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

14 Jan, 26

Salary

0.0

Posted On

16 Oct, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Data Science, Software Development, SQL, NoSQL, Python, ETL, Data Pipeline Design, Cloud Platforms, Data Validation, Collaboration, Problem Solving, Analytical Skills, Database Management, Technical Documentation, Data Governance, Quality Assurance

Industry

Farming

Description

Company Description "Join Syngenta Group, a leader in agricultural innovation where technology meets purpose. As digital pioneers in AgTech, we're integrating AI across our value chain from smart breeding to precision agriculture. Our global team of 56,000 professionals is transforming sustainable farming worldwide. At Syngenta IT & Digital, your expertise will directly impact food security and shape the future of agriculture through cutting-edge technology." Syngenta is one of the world’s leading agriculture innovation company (Part of Syngenta Group) dedicated to improving global food security by enabling millions of farmers to make better use of available resources. Through world class science and innovative crop solutions, our 60,000 people in over 100 countries are working to transform how crops are grown. We are committed to rescuing land from degradation, enhancing biodiversity and revitalizing rural communities. 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. To learn more visit: www.syngenta.com Job Description Purpose Develop and maintain robust data pipelines and infrastructure to support the creation of a supply chain digital twin. Enable accurate, real-time, and predictive insights by integrating and transforming data from diverse sources. Collaborate with cross-functional teams to enhance supply chain visibility, performance, and decision-making through advanced data engineering practices. Accountabilities Design and implement data pipelines to integrate real-time and historical data from multiple sources, including IoT devices, ERP systems, and external data feeds, into the digital twin environment. Assist with data extraction, transformation, and loading (ETL/ELT) processes using modern tools and frameworks. Ensure the accuracy, completeness, and timeliness of data feeding into the digital twin by implementing robust data validation, monitoring, and quality assurance processes. Collaborate with supply chain analysts and simulation experts to model and optimise the digital twin, enabling predictive insights and decision-making for supply chain performance improvements. Collaborate with data analysts, data scientists, and stakeholders to understand data requirements and provide technical support. Develop and maintain technical documentation for data processes and infrastructure. Assist in implementing and maintaining data governance and security best practices. Contribute to the optimisation of databases and query performance. Support the integration of third-party data sources and APIs. Participate in team code reviews, ensuring quality and adherence to standards. Stay up to date with emerging technologies, tools, and best practices in data engineering. Knowledge, Experience & Capabilities Required Knowledge & Technical Skills Strong problem-solving and analytical skills. Proficiency in Microsoft Office: Word, Excel, PowerPoint, SharePoint, Teams. Experience using virtual meeting & facilitation tools, such as Zoom, Mural/LucidChart/Miro, Menti, is advantageous. Required Experience Previous internship, placement, or project experience in data engineering, data science, software development, or a related field (desirable). Familiarity with database design, management and querying (SQL, NoSQL & Cypher). Exposure to cloud platforms such as AWS, Azure, Google Cloud, or Data Bricks (preferred but not essential). Critical Success Factors Excellent communication and collaboration abilities to work within a team environment. Eagerness to learn and adapt to new tools and technologies in a fast-paced environment. Ability to manage a busy workload and multiple tasks, balancing parrallel projects through effective organisation and time management skills to ensure desired outcomes are fully achieved on time. Complete activities to a high standard, demonstrating a consistently high level of attention to detail. Qualifications Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related discipline (or equivalent practical experience). Proficient in using SQL for designing, developing, and optimising queries to manage and manipulate data effectively Skilled in Python programming for data analysis, automation, and developing efficient solutions, with experience in libraries such as Pandas, NumPy, and SQLAlchemy to support data-driven projects. Understanding of ETL processes and data pipeline design. Basic knowledge of data modelling, warehousing, and big data technologies. Additional Information Note: 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, gender identity, marital or veteran status, disability, or any other legally protected status. Follow us on: Twitter & LinkedIn https://twitter.com/SyngentaAPAC https://www.linkedin.com/company/syngenta/ India page https://www.linkedin.com/company/70489427/admin/

Responsibilities

Develop and maintain robust data pipelines and infrastructure to support the creation of a supply chain digital twin. Collaborate with cross-functional teams to enhance supply chain visibility, performance, and decision-making through advanced data engineering practices.