Trend Analysis & Reporting: Conduct exploratory data analysis using in-house systems to spot patterns, diagnose performance gaps, and automate recurring reports.
The Data Engineer designs, builds and maintains data pipelines, integrations and data structures that support AI, machine learning, analytics and automation solutions. The role works with approved enterprise data platforms, including Databricks and Microsoft Fabric (medallion architecture), to ensure data is reliable, secure, well-governed and ready for approved technical and business use cases.
Supporting marketing initiatives across project and campaign lifecycles, including measurement plans, primary and secondary research and performance reporting
We do extensive data work across web3 and decentralized assets and prior experience and understanding of both how to access and interpret these technologies is strongly preferred
Analyze service uptime, incident trends, and support ticket volumes to identify patterns, forecast future demand, and provide insights to support capacity planning and operational improvements.
ML Training Integration: Keep GPU clusters fed using sharded training formats (WebDataset, Mosaic Streaming), caching, and optimized cross-region transfers.
Ensures tags associated to the documents are progressively built in the Client’s information management system master tag database, checking and verifying the quality of the imported tags and data attributes.