Syngenta Group Hiring Data Engineer in Pune | ₹8L–₹12L

About the Role

The Data Engineer will help build the data foundation behind Syngenta's supply chain digital twin. If you're unfamiliar with the concept, think of it as a virtual replica of real-world supply chain operations. It uses real-time and historical data to simulate performance, predict bottlenecks, and help teams make better decisions.

Your job is to ensure that the data powering this system is accurate, timely, and accessible. That means designing pipelines, integrating multiple data sources, and maintaining reliable infrastructure. Some days will involve building ETL workflows. Other days might focus on improving database performance or troubleshooting data quality issues.

Now, here's the interesting part. The role is highly collaborative. Data engineers here don't operate in isolation. You'll work closely with supply chain analysts, data scientists, and simulation experts who rely on your pipelines to run advanced models and predictive simulations.

The end result? Better supply chain visibility and faster decision making across global operations.

What You'll Work On

A large portion of the role focuses on building and maintaining data pipelines. These pipelines bring together information from many sources including IoT devices, enterprise resource planning systems, and external data providers. Some streams arrive continuously in real time. Others arrive in structured batches.

You'll transform that raw information into reliable, structured datasets ready for analytics and modeling. Clean data isn't optional here. It directly influences how well the digital twin can simulate real-world scenarios.

Another part of the job involves performance optimization. Large-scale datasets can slow down systems if they're not managed correctly. You'll tune queries, optimize databases, and ensure pipelines run efficiently even as data volume grows.

Documentation matters too. Engineers across teams depend on clear technical documentation to understand how pipelines operate and where data originates.

Key Responsibilities

• Design and maintain data pipelines that combine real-time and historical data from multiple internal and external sources.
• Build and support ETL or ELT workflows that transform raw data into structured datasets ready for analysis.
• Integrate data streams from IoT devices, ERP systems, and third-party APIs into the digital twin platform.
• Implement validation checks and monitoring systems to maintain high data accuracy and reliability.
• Work closely with analysts and simulation specialists to support predictive supply chain models.
• Improve database structures and query performance to support growing datasets.
• Assist with data governance practices and security standards across engineering workflows.
• Maintain clear documentation for pipelines, transformations, and system architecture.
• Participate in peer code reviews to maintain quality and consistent engineering standards.
• Explore emerging tools and frameworks that improve scalability and reliability of data infrastructure.

Team Environment

Expect a collaborative environment with people from multiple disciplines. Data scientists focus on modeling and prediction. Analysts translate results into business insights. Engineers like you build the systems that make everything possible.

Communication matters. You'll frequently discuss requirements, troubleshoot pipeline issues, and help stakeholders understand how data flows through the system.

The pace can be fast at times. Supply chains evolve quickly, and data systems must adapt just as fast. That said, teams place strong emphasis on thoughtful engineering and maintainable architecture rather than quick fixes.

Why This Role Stands Out

Working on a supply chain digital twin gives engineers exposure to real-world operational challenges. You're not just moving data from one system to another. You're helping create a predictive environment that allows companies to simulate scenarios before they happen.

And in agriculture, that impact reaches far beyond software dashboards. Improved supply chain efficiency can reduce waste, improve crop availability, and support farmers across the globe.

If you enjoy solving data problems, building reliable systems, and collaborating with diverse technical teams, this role offers a meaningful place to grow your engineering career.