Data Platform Engineer Manager

Syngenta Group; Pune District; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Syngenta in Pune invites an Engineering Lead for Data & Analytics to steer the Data Mesh platform, oversee product delivery, and advance AI, BI, and agentic analytics capabilities across the organization.

You will lead Databricks-based data engineering initiatives, collaborate with data science, analytics, and IT teams, ensure security and quality, and drive scalability, governance, and rapid experimentation.

Qualifications

• 5+ years of experience in data engineering, data platform engineering, or architecture.
• 3+ years hands-on experience with Databricks in production environments.
• Databricks Certified Professional or equivalent certification.

Responsibilities

• Design, build, operate, and improve an enterprise-scale Databricks-based data mesh platform.
• Focus on platform reliability, scalability, security, and enabling data engineers, analytics, and data science teams.

Skills

Databricks

Python

PySpark

Scala

Azure

AWS

GCP

Terraform

CI/CD

DevOps

Data governance

Education

B.Tech / M.Tech

Tools

Databricks Lakehouse

Spark SQL

Delta Lake

Unity Catalog

Job description

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 IT & Digital team is seeking a Engineering Lead - Data & Analytics in Pune. This role will support the delivery for leading data and engineering teams within our Data Mesh platform, oversee product delivery, and spearhead the modernization of our AI, BI, and agentic analytics solutions.

Job Description

• The Data Platform Engineer Manager is responsible for designing, building, operating, and continuously improving enterprise‑scale , Databricks based data mesh platform at Syngenta.
• This role focuses on platform reliability, scalability, security, and enablement of data engineers, analytics, and data science teams , enable domain autonomy to ingest, process, and share data usingDatabricks , while ensuring security, quality, and interoperability.

Knowledge, experience & capabilities

• Databricks Ecosystem:Expert-level knowledge of Databricks Lakehouse, Spark SQL, Delta Lake, Unity Catalog etc.
• Programming:Proficiency in Python, PySpark, or Scala for ETL/ELT development.
• Cloud Platforms:Hands-on experience with at least one major cloud provider (Azure, AWS, or GCP) and related data services. AWS Preferable.
• DevOps & Infrastructure-as-Code (IaC):Familiarity with Terraform, CI/CD pipelines, and DevOps practices.
• Data Governance:Experience with implementing data lineage, PII anonymization, and data quality frameworks.

Critical success factors & key challenges

• Strong data engineering skills , logical and reasoning
• Ability to deliver POCs, MVPs, Experiments, technology evaluations following design thinking practices
• Ability to orchestrate efforts needed to prioritize business initiatives across complex change agendas
• Excellent communication and stakeholder management skills to explain technical information to individuals who don't have the same technical background
• Problem solving and decision making skills
• Teamwork, team management and leadership skills

Qualifications

Qualification & Experience Level

• B.tech/M.tech
• 5+ yearsof experience in data engineering, data platform engineering, or architecture.
• 3+ yearsof hands-on experience specifically with Databricks in production environments.
• Certifications:Databricks Certified Professional

Additional Information

Innovations

Employee may, as part of his/her role and maybe through multifunctional teams, participate in the creation and design of innovative solutions. In this context, Employee may contribute to inventions, designs, other work product, including know-how, copyrights, software, innovations, solutions, and other intellectual assets.