Senior Data Quality Engineer
Role details
Job location
Tech stack
Job description
We are seeking a highly skilled and passionate Data Quality Engineer to play a pivotal role in shaping the trustworthiness and reliability of our data landscape within our evolving Data Mesh, specifically leveraging our Google Cloud Platform (GCP) ecosystem. In this role, you will be instrumental in defining, implementing, and evangelizing data quality standards and practices across our federated data ecosystem. You will empower domain teams to take ownership of their data product quality, building tools and frameworks that ensure data products are discoverable, addressable, inherently trustworthy, self-describing, and secure.
The successful candidate will have the opportunity to shape Bunge's data quality framework, influence data-driven decision-making at all levels of the company and contribute to the organization's overall digital transformation journey.
This is not a role about centralizing data quality checks, but about enabling a distributed and automated framework where quality is embedded at the source and throughout the data product lifecycle, with a strong focus on GCP-native quality and GenAI solutions.
Main Accountabilitie:
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Collaborate with Data Governance and Data Product Owners to define and evolve global data quality standards, policies, and metrics aligned with our Data Mesh principles.
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Advise on data contract design to embed quality expectations and validations at the point of data production, leveraging GCP services for enforcement.
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Champion a data-as-a-product mindset, ensuring data quality is seen as a core attribute of product excellence across GCP data products.
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Design, develop, and maintain self-serve data quality frameworks (DQaaS)., libraries, and tools that empower domain teams to implement, monitor, and enforce quality checks on their own data products within the GCP environment.
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Define and implement the strategy in Data Observability and Self-service consumption at scale to cover all data products in the Platform.
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Contribute to the design and evolution of the overall GCP-based Data Platform's capabilities related to data quality, observability, and metadata management, specifically for services like BigQuery, Cloud Storage, Dataflow, Dataproc, and Pub/Sub.
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Evaluate and recommend new data quality technologies and tools that align with our Data Mesh vision and integrate seamlessly with our existing GCP ecosystem.
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Communicate regularly with stakeholders on data quality progress, challenges, and opportunities.
Requirements
- Bachelor's degree in computer science, Information Management, or a related field.
- Minimum of 5 years of experience in Data Quality Engineering, Data Engineering, or a related data role with a strong focus on data reliability.
- Proven track record of designing and implementing data quality frameworks at scale within a GCP environment, ideally applying DataOps practices.
- NIce to have: Experience building multi-agent systems or orchestrations
- Hands-on experience in building data quality solutions within Data Mesh architecture.
- Relevant GCP certifications (e.g., Professional Data Engineer, Cloud Architect, Data Analytics Specialization) are highly preferred.
- Deep understanding of Data Platform, Data Products, and Data Mesh principles, with practical experience in implementing distributed data quality.
- Strong knowledge with hands-on experience in data quality management processes and techniques, including data profiling, validation, monitoring, and remediation.
- Expertise in Google Cloud Platform (GCP) data services is essential, including:
- Proficiency in Python for data manipulation, API, scripting, and building data quality tools.
- Experience in prompting engineering to define data quality rules using some of LLM in the market
- Strong SQL skills and experience writing complex queries for BigQuery and other data stores.