Job Description

Role: Data Modeller

Location: Wilmslow (Hybrid - 2/3 days per week onsite)

Duration: 6 Months

Day rate: Negotiable inside IR35

Role Description:

Applies wide data modelling knowledge at all levels (conceptual, logical and physical), plus physical warehouse data structured design experience within an Agile development environment.

Working potentially over multiple projects at any one time, so ability to multi-task and balance competing priorities important.

Chairs data model design review sessions when required

Maintains data modelling standards and reviews data model design for compliance.

Present to the Data Design Authority (or other design authority bodies) when required on data modelling\design related topics.

Defines the data mapping and transforms from source to target entities in the data model, working closely with data engineers, source system SMEs and technical BAs.Required Skills:

Expertise: Demonstrable experience and expertise of all levels of data modelling - conceptual, logical and physical and the various data design approaches used in modern data platform such as relational, dimensional, data-vault and de-normalised big table and the correct application of each approach.

Proven Experience: Demonstrates a proven track record in data modelling for complex, multi-vendor programmes and matrix-led engagements.

Pragmatic approach: always focused on delivering business value and balancing the trade-offs between design purity and value delivery.

Excellent interpersonal skills: ability to clearly explain complex data modelling and data design concepts to others in the technical team and those in senior less technical roles.

Ability to work closely with third-party authorities and MSA suppliers\partners and has a good understanding of regulations and legislation within the financial services market.

Technical Proficiency: Skilled in using data modelling tools (Idera ER/Studio or similar such as Erwin). ETL\Data pipeline exposure, ideally with hands on experience on a number of integration tools such as Azure Data Factory and Qlik.

Expert level SQL skills.

Exposure to Azure Databricks and Databricks Notebooks (optional)