About the project: This is a cutting-edge patent analytics software designed to transform the way intellectual property is evaluated. By integrating high-quality patent datasets with scientifically validated metrics, it introduces a data-driven approach to patent valuation—challenging the traditional, subjective methods commonly used in the industry. The platform enables users to gain deeper insights into patent quality, technological relevance, and competitive positioning, providing a more objective foundation for strategic decision-making in innovation and IP management.
Talent you’ll bring into our team: * 2+ years building and optimizing large‑scale data platforms in cloud environments (AWS/Azure) * Knowledge of Python and SQL for analytical workloads * Familiarity with modern Lakehouse / streaming architectures and tools such as Databricks, Snowflake, Kafka, Spark * Ability to translate business requirements into resilient, scalable data solutions and to mentor peers through code reviews and best‑practice evangelism * Upper-Intermediate or higher level of English for effective communication within the team
Nice-to-Have Skills: * Experience with search technologies (Elasticsearch, Solr) and complex IP or litigation data models * Hands‑on work with external patent‑data sources (DocDB, Espacenet, USPTO) * Pandas / PySpark for exploratory analysis and rapid prototyping * Knowledge of Delta Share, data‑product versioning and governance frameworks
Responsibilities: * Build and maintain data pipelines for processing large volumes of structured and unstructured data in both batch and real-time * Use Lakehouse patterns to combine data lake and warehouse capabilities for ML features and analytics * Design APIs with built-in lineage tracking and access control for use across different business units * Apply DataOps practices to automate testing, deployment, monitoring, and lifecycle management * Promote clean code, code reviews, and A/B testing to improve data product quality. * Work closely with ML engineers, developers, and domain experts to refine requirements and solve technical challenges * Stay up to date with new tools and trends in data engineering to improve performance, scalability, and developer experience
Benefits program: * Paid vacation, paid sick leaves, 10 Public holidays, additional days off * Educational budget and support in receiving certificates/attending conferences, etc. * English lessons
Comfortable Working conditions: * Flexible working hours * Amortization program or provision of required equipment
