We are seeking a hands-on senior data warehouse architect to help us build out and manage our data warehouse and surrounding systems, which will need to operate reliably at scale using a high degree of automation in setup and maintenance. The focus of the role will be on taking ownership of the data warehouse data model design and implementation, data ingestion, data lineage, data quality and data governance. This will be within the context of a cloud-native data platform consisting of both batch and streaming pipelines, but which prioritises event streaming based data acquisition and processing.

The individual will also need to be able to manage multiple stakeholders at an executive level and make well informed architectural choices when required. A high degree of empathy is required for the needs of the downstream consumers of the data artefacts produced by the data engineering team, i.e. the software engineers, data scientists, business intelligence analysts, etc and the individual needs to be able to produce transparent and easily navigable data pipelines. Value should be assigned to consistently producing high quality metadata to support discoverability and consistency of calculation and interpretation. 

A solid understanding of the retail banking domain is highly desirable. 

Candidates should have a wide set of experience across the following systems and languages:

  • Ideally GCP, but strong experience in another platform such as AWS or Azure will suffice
  • Cloud data warehouses such as BigQuery, Redshift or Snowflake
  • Data warehousing concepts such as Star Schema and Snowflake
  • Fluency in materializing data warehouse schema and relation through ER diagrams
  • Good understanding of relational databases as well as NoSQL databases such as MongoDB
  • Highly proficient in SQL
  • Event streaming platforms such as Kafka
  • Workflow scheduler such as Apache Airflow
  • Familiarity with Kubernetes
  • Python and Java.
  • Comfortable writing detailed design documents

 

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