In today's digital age, instant information is the norm. But this transparency disappears when it comes to consumer products, and their ethical and sustainable production through supply chains. Addressing the global climate challenge and safeguarding both humanity and the planet requires a transformation in food systems.
This is why we built OpenSC.
Co-founded by WWF and The Boston Consulting Group, OpenSC is on a mission to revolutionize the way we buy and produce products by providing data on transparency and traceability for supply chains.
We deliver social and environmental impact by providing supply chain transparency that empowers brands to know, influence, and prove the sustainability of their supply chain practices.
This is achieved through the OpenSC platform, which leverages AI, Blockchain and Remote Sensing technologies to enable automated ingestion, analysis, and sharing of a supply chain's data.
Tasks
- Further design and build OpenSC’s data platform across all data domains: collection, storage, transformation and analyses
- Develop high-quality data pipelines that transform structured, semi-structured, and unstructured data from various sources into a standardized data model
- Expand OpenSC’s data model to accommodate a growing number of use cases
- Assume responsibility for the business interpretation of data and actively contribute to data science and analytics projects
- Provide support and guidance on data security and cloud infrastructure topics, ensuring a secure and efficient handling of data
- Adhere to software engineering best practices regarding version control, testing, code reviews, deployment etc.
- Communicate effectively with technical and non-technical stakeholders
- Contribute elevating the team through knowledge sharing on data engineering best practices
Requirements
- 6+ years of relevant industry experience building production-level data products
- Proven solid foundation of core data concepts (e.g. integration, modeling, security, lineage, governance etc.)
- Excellent Python skills and advanced competencies with main data ecosystem libraries (pandas, great expectations, dbt etc.)
- Advanced knowledge of SQL and relational databases (e.g. PostgreSQL)
- Extensive experience with data pipeline orchestration tools (e.g. Dagster, Airflow, etc.)
- Extensive experience working with cloud infrastructure and services (ideally on AWS)
- Experience working with different data modeling patterns and ability to abstract complex real-life information into a standardized data model description
- Demonstrated familiarity with Version control (Git), Containerization (Docker, Kubernetes), CI/CD (e.g. CircleCi, Github Actions), IaC (Terraform)
- Strong interpersonal skills and ability to work in a multidisciplinary and multicultural team
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