Data Platform Engineer Manager

Syngenta · Pune/Pimpri-Chinchwad Area

  • Experience5–6 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelsenior
  • Posted15 Sept 2026
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About Syngenta

Syngenta is hiring in Pune/Pimpri-Chinchwad Area in agriculture food. This role looks for around 5+ years of experience.

Skills

  • Databricks Lakehouse
  • Spark SQL
  • Delta Lake
  • Unity Catalog
  • Python
  • PySpark
  • Scala
  • AWS
  • Azure
  • Google Cloud Platform
  • Terraform
  • CI/CD
  • DevOps
  • Data Lineage
  • PII Anonymization
  • Data Quality Frameworks
  • Databricks Certified Professional

The role

A data platform engineer at an agricultural technology company designs and operates Databricks Lakehouse data mesh platforms, enabling enterprise data engineering and analytics through Spark SQL and Delta Lake. The role also applies Python and PySpark to build scalable data pipelines and supports secure, governed data sharing.

Full job description

Company 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

Role purpose

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 using Databricks, 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 practicesAbility to orchestrate efforts needed to prioritize business initiatives across complex change agendasExcellent communication and stakeholder management skills to explain technical information to individuals who don't have the same technical backgroundProblem solving and decision making skillsTeamwork, team management and leadership skills

Qualifications

Qualification & Experience Level

B.tech/M.tech5+ years of experience in data engineering, data platform engineering, or architecture.3+ years of 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.