Principal Data Engineer - Technical Lead
Overview
Bunge has an exciting opportunity available for a Principal Data Engineer - Technical Lead. In this role you will be part of a integral team working on challenging, meaningful projects impacting core business activities.
The Principal Data Engineer - Technical Lead is a critical leadership role within Bunge's Global IT organization. You will lead and inspire a team of talented data engineers responsible for building and maintaining Bunge's next-generation Data Platform. This platform will empower data-driven decision-making across the company, fueling innovation and operational efficiency in areas such as supply chain optimization, risk management, and market analysis. This role requires a strategic thinker with strong technical expertise and a passion for building high-performing teams. You will navigate the challenges of a complex global environment while capitalizing on opportunities to leverage cutting‑edge technologies to transform Bunge's data landscape. On this role you will be also a hands‑on technical person and a leader of a team of data engineers.
Essential Functions
- Provide mentorship, coaching, and career development guidance to a team of Data Engineers, fostering a culture of collaboration, innovation, and continuous learning.
- Collaborate with stakeholders to define and execute a long-term vision for Bunge's data platform, ensuring alignment with business objectives and industry best practices.
- Lead the design, development and implementation of a scalable, secure and reliable data platform, leveraging cloud technologies and modern data engineering principles.
- Implement and enforce data governance policies and procedures to maintain data accuracy, consistency and compliance with regulatory requirements.
- Continuously monitor platform performance, identify areas for improvement and implement optimization strategies to ensure high availability, scalability and cost-effectiveness.
- Build strong relationships with business stakeholders, data scientists and other IT teams to understand data needs and ensure the platform meets their requirements.
- Research and evaluate emerging technologies and trends in data engineering and platform development, recommending and implementing innovative solutions to enhance Bunge's data capabilities.
- Influences data strategy and operations across Bunge's global footprint.
- Directly impacts data-driven decision-making across all business units.
- Manages a team of Data Engineers.
- Be recognized as an external thought leader at Data Engineering and Lake-House architecture in Google Cloud.
- Help shape Data Platform roadmap and vision.
- Influence the future direction of Bunge's data platform architecture.
- Lead the adoption of cutting‑edge data technologies.
- Develop and mentor a high-performing engineering team.
- Ensure an excellence in the Data Platform operation at global scale.
- Lead Data Strategy and Data Modeling in the Bunge Data Platform.
- Leads technical discussion across other data Engineer to ensure best practices, approaches, and implementation.
- Contributes to talent management plans to support business strategies.
Qualifications
- Bachelor's degree in Computer Science, Information Technology, or related field. Master's degree preferred.
- 7+ years of experience in data engineering, with at least 3 years in a management role.
- Experience building and managing large-scale Data Platforms in a cloud environment.
- Proven ability to lead and develop high-performing engineering teams.
- Excellent communication, interpersonal and stakeholder management skills.
- Cloud Platforms: GCP (Preferred), AWS or Azure.
- Data Engineering Tools: Very strong and hands‑on experience in Google Cloud Data Analytics: Big Query, DataStream, DataProc.
- Skilled in SQL, Python, and DBT/DataForm.
- Experience in complex event‑driven data pipeline orchestrations.
- Data Warehousing and Data Lake Technologies: BigQuey (Preferred), Snowflake.
- Data Governance and Security: Best practices and implementation in Cloud Environments.
- Software Development Lifecycle (SDLC): Agile methodologies.
- Experience in IaC in Data using Terraform.
- Deep understanding of data mesh concepts and modern Lake-House data Architecture.
- Deep understanding of Kappa Architecture and experience in CDC ingestion.
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