Job Description

Description of role and key responsibilities


The candidate will be required to deliver to all stages of the data engineering process - data ingestion, transformation, data modelling and data warehousing, and build self-service data products. The role is a mix of Azure cloud delivery and on-prem (SQL) development. Ultimately all on-prem will be migrated to cloud and decommissioned - but we are only part way along that journey.



There will be a dual reporting line between the main business technology area (Asset Lending) providing the day-to-day direction and management of work items, and the Head of Data for Corporate Banking Technology - who will provide guidance on overall Data strategy and alignment with wider bank.



The role itself will work closely with our Architect, Engineering lead, Analytics team, DevOps, DBAs, and upstream Application teams in Asset Finance, Working Capital and ABL.



Specifically, the person will:


Work closely with end-users and Data Analysts to understand the business and their data requirements Carry out ad hoc data analysis and 'data wrangling' using Synapse Analytics and Databricks Building dynamic meta-data driven data ingestion patterns using Azure Data Factory and Databricks Build and maintain the Enterprise Data Warehouse (using Data Vault 2.0 methodology) Build and maintain business focused data products and data marts Build and maintain Azure Analysis Services databases and cubes Share support and operational duties within the wider engineering and data teams Work with Architecture and Engineering teams to deliver on these projects. and ensure that supporting code and infrastructure follows best practices outlined by these teams. Help define test criteria to establish clear conditions for success and ensure alignment with business objectives. Manage their user stories and acceptance criteria through to production into day-to-day support Assist in the testing and validation of new requirements and processes to ensure they meet business needs
Stay up-to-date with industry trends and best practices in data engineering



Core skills and knowledge


Excellent data analysis and exploration using T-SQL Strong SQL programming (stored procedures, functions) Extensive experience with SQL Server and SSIS Knowledge and experience of data warehouse modelling methodologies (Kimball, dimensional modelling, Data Vault 2.0) Experience in Azure - one or more of the following: Data Factory, Databricks, Synapse Analytics, ADLS Gen2 Experience in building robust and performant ETL processes Build and maintain Analysis Services databases and cubes (both multidimensional and tabular) Experience in using source control & ADO Understanding and experience of deployment pipelines Excellent analytical and problem-solving skills, with the ability to think critically and strategically. Strong communication and interpersonal skills, with the ability to engage and influence stakeholders at all levels. To always act with integrity and embrace the philosophy of treating our customers fairly Analytical, ability to arrive at solutions that fit current / future business processes Effective writing and verbal communication Organisational skills: Ability to effectively manage and co-ordinate themselves. Ownership and self-motivation Delivery focus Assertive, resilient and persistent Team oriented Deal well with pressure and highly effective at multi-tasking and juggling priorities
Any other attributes that would be helpful, but not essential for the role.


Deeper programming ability (C#, .Net Core) Build 'infrastructure-as-code' deployment pipelines Asset Finance knowledge Vehicle Finance knowledge ABL and Working Capital knowledge
Any financial services and banking experience