Senior Data Engineer at Syngenta Group

pune, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

03 Feb, 26

Salary

0.0

Posted On

05 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Databricks, SQL, Python, ETL, Data Quality, Data Governance, Cloud Platforms, SAP, Data Warehousing, Data Modeling, CI/CD, Version Control, AI, Technical Guidance, Data Integration

Industry

Farming

Description

Company Description Join Syngenta Group, a leader in agricultural innovation where technology meets purpose. As digital pioneers in AgTech, we're integrating AI across our value chain from smart breeding to precision agriculture. Our global team of 56,000 professionals is transforming sustainable farming worldwide. At Syngenta IT & Digital, your expertise will directly impact food security and shape the future of agriculture through cutting-edge technology. Website address - https://www.syngentagroup.com/ Job Description Purpose The Senior Data Engineer plays a pivotal role in driving the design, development, and optimization of robust, scalable, and high-performance data products and pipelines on Databricks (Spark/Delta Lake/Unity Catalog). This role is critical in enabling a domain-oriented data mesh architecture, ensuring exceptional data quality, governance, reliability, and cost efficiency. As a Senior Data Engineer, you will not only build and maintain complex data solutions but also provide technical provide technical guidance and support to junior engineers and contribute to best practices across the team as well as bridge towards business stakeholders, translating complex business requirements into technical solutions and effectively communicating technical concepts and challenges to non-technical audiences. You will actively contribute to the technical evolution of our Data Mesh, driving business impact through AI ready data. Additionally you will be critical in the process of onboarding emerging technologies like SAP Business Data Cloud and Data Sphere. Accountabilities Design, develop, and optimize complex data pipelines and model AI ready data products using Databricks and potentially later in SAP Business Data Cloud, ensuring scalability, reliability, and performance. Implement and refine advanced ETL/ELT processes, adhering to best practices and optimizing for efficiency and data integrity. Act as a liaison with business stakeholders, proactively engaging to understand complex requirements, clarify definitions, identify issues, and effectively communicate technical challenges and solutions in an accessible manner. Conduct thorough code reviews, provide constructive feedback, and ensure adherence to high software engineering standards and technical documentation practices. Provide technical guidance and support to junior and mid-level data engineers, fostering a culture of continuous learning and technical excellence. Champion data quality and governance standards, implementing robust monitoring and validation frameworks. Actively participate in architectural discussions and contribute to the technical evolution of the data mesh and data product strategy, including evaluating and integrating new technologies. Design and implement data integration solutions with such as SAP S/4HANA, BW/4HANA, ECCs, Workday, ONIT, etc. ensuring seamless data flow and accessibility. Professional Experience: 9+ years of progressive experience in data engineering, with a significant portion in a senior individual contributor capacity delivering data products. Proven track record of successfully delivering complex data engineering projects from inception to production. Experience in engaging with non-technical audiences as well as guiding and supporting junior engineers and contributing to technical initiatives. Multiple years of business or IT experience, ideally related to corporate functions (Finance, HR, Procurement, Legal). Technical Expertise: Expert-level proficiency in SQL and Python (including PySpark), with a strong emphasis on modular code, testing, and robust software engineering practices. Deep hands-on expertise with Databricks on cloud: Spark, Delta Lake, Unity Catalog, Delta Live Tables, Workflows, Repos/CLI, Asset Bundles. Familiarity with MLflow is a plus. Extensive experience with data warehousing and lakehouse patterns, advanced dimensional and domain-oriented data modeling, and complex ETL/ELT design and orchestration using platforms like Fivetran, Snaplogic or Glue Demonstrated experience extracting and transforming data from SAP S/4HANA, SAP BW/4HANA, ECC, and related systems (IDocs, BAPIs, OData services). Direct experience with SAP Business Data Cloud and Data Sphere is highly desirable. Proficiency with version control systems (Git, preferably GitLab) and advanced branching/merge request workflows. Expertise in CI/CD pipelines and deployment automation for data platforms. Strong understanding and practical application of data quality principles, data governance, and data security. Experience with cloud platforms (AWS preferred) and their data-related services. Qualifications Bachelor's or Master's degree in Computer Science, Information Systems, or a related Data & Analytics field. Additional Information Note: Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity, marital or veteran status, disability, or any other legally protected status. Follow us on: LinkedIn LI page - https://www.linkedin.com/company/syngentagroup/posts/?feedView=all

Responsibilities

The Senior Data Engineer is responsible for designing, developing, and optimizing complex data pipelines and AI-ready data products. This role also involves providing technical guidance to junior engineers and engaging with business stakeholders to translate complex requirements into technical solutions.