Design and drive the implementation of a data hose from Ebury production that integrates data models coming from relational and non-relational sources for BI consumption, working with Data team and Tech team
Analyses and identifies performance bottlenecks within our current Ebury back office system data architecture
Working with the SRE team ensures high availability and performance of our data storage solutions
Define and implement a strategy to decouple data processing for BI from Data models used in production
Research and develop PoC for quasi-real-time data pipelines
Contribute to the product roadmap to drive work through tech teams
Responsible for the high availability of the API
Must Haves
Proven experience building data pipelines from live production environments
Proven experience on optimizing SQL database performance including CQRS patterns
Experience designing and implementing building real-time data pipelines and streaming solutions
Strong backend development track record (python)
Experience defining work for engineering teams to implement (product stories)
Nice to Have
Managed large Database infrastructure deployments
Comes from the Financial sector
Postgres optimisation
AWS Data pipeline infrastructure, Django signals, airflow and aws kinesis, Kafka, flink or spark