Syngenta Group
agriculture
DataPlatformEngineerManager
Neural analysis suggests this role is
optimal for mid candidates.
“Data Platform Engineer Manager at Syngenta Group. Skills: Databricks, Data Mesh, Data Engineering. Designing data mesh platform. Building data mesh platform”
Industry & Context.
Problem solving skills; decision making skills
What They're Looking For.
Must Have
5+ years of experience in data engineering, data platform engineering, or architecture, 3+ years of hands-on experience specifically with Databricks in production environments
Nice to Have
Databricks Certified Professional
What You'll Do.
Designing data mesh platform
Building data mesh platform
Operating data mesh platform
Improving data mesh platform
Enablement of data engineers
Enablement of analytics teams
Enablement of data science teams
Ensure interoperability
Oversee product delivery
Modernize AI solutions
Modernize BI solutions
Modernize agentic analytics solutions
How You'll Work.
Team & Collaboration
collaborative team; work closely with product; stakeholder management skills; teamwork; team management; leadership skills
Communication Scope
Excellent communication skills; explain technical information
Process & Methodology
Ability to orchestrate efforts, Ability to prioritize business initiatives
Full 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. 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](https://www.databricks.com/), 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 inf
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