Senior Data Architect

Bunge Iberica SA; Cataluña; Híbrido; EUR 60.000 - 100.000; Jornada completa

Descripción de la vacante

An established industry player is seeking a Senior Data Architect to join their innovative Data Platform team. This role is pivotal in modeling new data products that empower data-driven decision-making across various business domains, including supply chain and risk management. You will collaborate with diverse teams to ensure data solutions are scalable and sustainable, while also defining master data and enforcing governance policies. This position offers a hybrid work environment, allowing for a balanced approach between remote and in-office collaboration. If you are passionate about leveraging data to drive innovation and operational efficiency, this opportunity is perfect for you.

Servicios

Generous paid time off program

Flexible work arrangements

Strong compensation and benefits package

Formación

• PhD or postgraduate degree in STEM with experience in Data Science.
• Expertise in SQL, data modeling, and proficiency in Python.

Responsabilidades

• Design and test data models that drive analytical solutions.
• Collaborate with cross-functional teams to implement data solutions.

Conocimientos

SQL

Data Modeling Techniques

Python

Analytical Skills

Teamwork

Communication Skills

Educación

PhD in a STEM field

Postgraduate degree in a STEM field

Herramientas

Collibra

DataHub

Atlas

Descripción del empleo

Location : Sant Just Desvern, B, ES, 08960

City : Barcelona

Country : Spain (ES)

Requisition Number : 39344

Bunge, a global leader in agribusiness, has an exciting opportunity available for a Senior Data Architect. As part of a global team, you will work on challenging and meaningful projects that directly impact core business activities. Since 1818, Bunge has been connecting farmers to consumers, delivering essential food, feed, and fuel to the world. Looking towards the future, Bunge aims to continuously reinvent itself, leveraging data to be at the forefront of analytics, technology, and talent to accomplish its purpose in a better, faster, and simpler way.

At Bunge, employees don't just come to work; they come to grow, solving challenges that directly impact the world with a diverse team of thinkers and doers. Bunge offers a strong compensation and benefits package, a generous paid time off program, flexible work arrangements, and opportunities for career progression. The hybrid work environment provides a balance between in-office and remote work.

Most importantly, Bunge lives its values in all that it does :

• Act as One Team : Fostering inclusion, collaboration, and respect
• Drive for Excellence : Being agile, innovative, and efficient
• Do What's Right : Acting safely, ethically, and sustainably

Overview

We are seeking a highly motivated and experienced Senior Data Architect as part of the Data Platform team. This platform will empower data-driven decision-making across the company, fueling innovation and operational efficiency in areas such as supply chain & logistics, risk management, Industrial Operation, corporate functions, or market analysis. As Senior Data Architect, you will be responsible for modeling new data products in a Data Mesh paradigm ensuring data solves business problems, communicating to the technical team building data products, and assuring the delivery matches business expectations. You will also be responsible for working with cross-functional teams to identify and prioritize the definition of new master data in the platform.

Essential Functions

• Act as a main point of contact and SME for all data architecture and modeling topics for a specific business domain : supply chain & logistics, risk management, Industrial Operation, corporate functions, or market analysis.
• Design, create, and test data models in data products that drive the reusability of analytical solutions throughout the organization.
• Provide technical support for data product teams building new data products.
• Collaborate with Business Analysts, Data Scientists, and Data Product Owners to understand business problems and implement scalable and sustainable data solutions.
• Define master data, data ontologies, and metadata management for data products and platform components.
• Coordinate with Data Product Owners and Data Governance teams to implement and enforce data governance policies and procedures to maintain data accuracy, consistency, and compliance with regulatory requirements.
• Make decisions aligned to Bunge’s global strategy, business needs, and financial goals while exploring new perspectives by driving innovation.
• Cultivate strong relationships and networks, effectively influence others, and develop talent to excel in their current and future roles.
• Develop data-driven strategies aligned with Bunge’s priorities, energizing others to action through clear and compelling communication.

Qualifications

• PhD in a STEM field with research experience in Data Science or a postgraduate degree in a STEM field with 3-5 years' experience as a Lead Data Scientist.
• Expert in SQL and data modeling techniques.
• Experience with Data Catalog and metadata management tools : Collibra (Preferred), DataHub, Atlas, etc.
• Proficient in data modeling techniques, SQL and Python, data analysis, analytical skills, teamwork, and communication skills.
• Advanced knowledge of analytics and computer science, knowledge of AI / ML and BI spaces.
• Experience in Data Platform and Data Mesh paradigm in mid or large enterprises.
• Capable of mentoring Associates and other Data Architects / Engineers and answering business questions to higher authorities and management related to the designated business domain.
• Model behavior as a great team player and teach new ideas.
• Communicate with project stakeholders on a regular basis.
• Assist business in structuring the problems / hypotheses they want to address and convert it into a data model implemented in a data product.
• Develop best practices and improve data-driven mindset awareness of possible use cases and help them to understand the necessary concepts of data modeling, data sharing in a Data Mesh architecture and ensure better communication and understanding across functions.