Data Platform Engineer Manager at Syngenta Group

pune, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

23 Aug, 26

Salary

0.0

Posted On

25 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Databricks Lakehouse, Spark SQL, Delta Lake, Unity Catalog, Python, PySpark, Scala, AWS, Terraform, CI/CD, Data Governance, Data Mesh, ETL/ELT, Stakeholder Management, Team Leadership, Design Thinking

Industry

Farming

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 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+ 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.

Responsibilities

Responsible for designing, building, and operating an enterprise-scale Databricks-based data mesh platform. The role focuses on platform reliability, scalability, and enabling domain autonomy for data ingestion and processing.