Experience designing and building end-to-end data pipelines and analytics layers
Strong Python development and data processing skills
Experience with data modeling, ETL/ELT processes, and data warehousing
Ability to translate backend data structures into business-ready visualizations and dashboards
Requirements:
Own and architect the end-to-end reporting lifecycle from ingestion to analytics delivery
Transform raw Python application data into a high-performance analytics layer
Bridge the gap between backend data structures and business-ready visualizations
Work with a replicated production environment to operate MVP-stage data pipelines
Job description
Client is developing a system of record for the diamond supply chain. A critical part of this is the diamond matching project.
We are seeking a Data Engineer to own and architect the end-to-end reporting lifecycle, that’s still in an early MVP stage. You will inherit a replicated production environment and be responsible for transforming raw Python application data into a high-performance analytics layer. You will bridge the gap between backend data structures and business-ready visualizations.
