Data Platform Engineer Manager
Syngenta Group Open · verified Oct 24, 2026 At a glance
Manager-level Data Engineering role at Syngenta Group. Pune · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Design and run the Databricks data mesh, improving its reliability, scale, security and ongoing operation
- Enable engineering, analytics and data science teams to ingest, transform and share data across domains
- Maintain data safeguards and consistency through lineage, PII anonymization and quality frameworks
- Guide platform delivery and modernization of AI, BI and agentic analytics solutions
- Develop proofs of concept, prototypes and technology assessments to help prioritize complex initiatives
What you bring
- At least five years in data engineering, platform engineering or data architecture
- At least three years using Databricks in production, with deep knowledge of its Lakehouse, Spark SQL and Delta Lake
- A B.Tech or M.Tech, plus a Databricks Certified Professional credential
- Hands-on Python, PySpark or Scala skills, experience with a major cloud provider, and familiarity with Terraform and CI/CD
Who this fits
This is a manager-level role based onsite in Pune, combining hands-on platform engineering with team leadership and stakeholder coordination. You’ll need to explain technical decisions to people with varied technical backgrounds.
From the employer
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.
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 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
Qualification & Experience Level
- B.tech/M.tech
- 5+ 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
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.
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