Data Quality Specialist

Company Description

Syngenta is a global leader in agriculture; rooted in science and dedicated to bringing plant potential to life. Each of our 28,000 employees in more than 90 countries work together to solve one of humanity’s most pressing challenges: growing more food with fewer resources. A diverse workforce and an inclusive workplace environment are enablers of our ambition to be the most collaborative and trusted team in agriculture. Our employees reflect the diversity of our customers, the markets where we operate and the communities which we serve. No matter what your position, you will have a vital role in safely feeding the world and taking care of our planet. Join us and help shape the future of agriculture. 

Job Description

The Data Quality Specialist works with the Seeds R&D Data Platforms Team and other business functions to facilitate the creation, maintenance, and validation of our strategic data assets. This role supports the deployment of established data quality practices, works with the Data Quality Lead to define quality measures and implement business rules needed to verify and validate R&D enterprise data. 

The Data Quality Specialist uses best practices and tools to analyze and measure data quality and develop action plans to ensure data reliability, completeness, and consistency. The Data Quality Specialist role will support the Data Governance team in driving governance policies across all R&D business functions and support compliance with required data standards.

Accountabilities

• Data Quality Specialist will partner closely with data creators, data stewards, data consumers, and IT to ensure our data is usable, timely, robust, trustworthy, and compliant. This role looks at the end-to-end data flow and lifecycle, from generation/acquisition to exploitation and value, to establish global and local data quality dimensions, rules, and indicators. 
• Support global and regional data owners, data stewards and SME's for data standardization, cleansing, and data migration activities
• Align Data Quality rules and policies to evolving data landscape and domains
• Leverage data quality best practices to design and maintain policies, methodologies, guidelines around data quality, data profiling, data cleansing, including KPI/metrics definitions
• Collaborate and support stakeholders responsible to implement relevant data quality rules and policies and ensure those rules and policies are implemented
• Evaluate, implement, and manage governance tool to track and manage data quality and compliance, support reconciliation and validation processes. 
• Collaborate with business users to identify attributes that require data quality and corresponding business rules. Profile data, analyze user requirements, and translate & apply business rules to data quality rules.

Qualifications

Required:

• Minimum 5 years of experience in data quality, including:
  • Developing dashboards through PowerBI, Tableau or similar
  • SQL (Python, Spark, AWS are nice to have)
  • Extensive experience applying data quality principles to deliver high-quality data assets
  • Data quality and management platforms, query and scripting languages
  • Identifying and resolving data quality issues
  • Performing root cause analysis on data quality issues.
  • Data integration and data profiling tools, automation of processes
  • Up-to-date expertise in data analysis with a strong focus on data quality and governance concepts

Preferred:

• Agriculture or biology background is a plus
• Tools such as Informatica, Colibra, DeeQu, etc.
• Experience with data standards and ontologies
• Interest and passion for working in a complex data domain and dynamic business environment, solving challenging problems, and supporting transformation
• Ability to work in complex, matrix environments doing hands-on work as the situation requires
• Ability to work with business and analytics leaders to identify solutions to data quality and successfully champion the role of data quality to preserve data integrity.
• Understanding of the data governance process, data stewardship, data cataloguing, data engineering, data integration, business rules management, etc.
• Ability to cultivate relationships with business partners to analyse and implement solutions to improve user experience.
• Ability to improve users' trust and confidence in the data products.
• Ability to demonstrate the direct impact of data quality checks and balances on business decisions.
• Ability to provide cost-saving and efficiency gain due to data quality improvement

Additional Information

What We Offer:

• Full Benefit Package (Medical, Denta