Overview

Data Engineer – Hybrid Working

£45,585 – £54,395

30 Days Holidays + 4 Days Christmas + Bank Holidays

Great Pension

Career Development

Flexible Working – (Hybrid)

A Great Working Environment

Excellent Sport & Leisure Facilities

Training and Personnel Development Offerings

Office Location is close to A45, A46, M1, M6, M40, M42, M69

Great Public Transport Links

We have a great opportunity for an experienced Data Engineer to join an established team within one of the UK’s leading universities.

As one of the Data Engineers within the team, you will be responsible for leveraging Azure Data Factory and DBT to design, develop, and maintain robust data pipelines and scalable data models which integrate data from a wide variety of structured and unstructured data sources across the university, ensuring appropriate security and utility of data.

The role will design analytical environments such as data marts, using a user centred design approach to meet a variety of reporting or analytical needs.

The role will also mentor users of various skill levels to engage with and succeed with their own use of the data products you help deliver. Directly contributing to enhancing data accessibility, quality, and analytics capabilities within the university.

Duties:

  • Technical work to model data and Design and Develop Data Pipelines
  • Undertake and manage the development of data models
  • Contribute to the design of data products and organise the backlog of work in planning tools like Jira
  • Utilise Azure Data Factory to design and develop scalable and efficient data pipelines
  • Utilise DBT (Data Build Tool) to create and manage data transformation processes, ensuring consistent and reliable data output
  • Design, implement and maintain DataVault and Kimball-style data models to ensure efficient storage, retrieval, and analysis of data by different user communities across the university.
  • Monitor and optimise the performance of data pipelines and data warehouses, identifying and resolving bottlenecks and inefficiencies.
  • Design and implement data security measures
  • Design and implement data quality checks and validation processes within the pipelines using expectations with the pipeline, or dedicated testing tools (SODA)
  • Collaborate with data governance, architects, system/product owners and end users to ensure quality issues are addressed as needed.
  • Create and maintain technical documentation, including data pipeline specifications, data models, and transformation logic
  • Contribute to data modelling and schema design standards and related documentation.

Qualifications & Requirements

  • Degree in Computer Science, Data Engineering, or a related field or equivalent experience
  • Strong experience working as a Data Engineer, preferably in a cloud-based environment.
  • Experience with cloud-based data storage platforms, preferably Snowflake, Azure SQL Data Warehouse or AWS Redshift.
  • Solid practical experience and understanding of DataVault and Kimball-style data warehousing methodologies.
  • Proficient in SQL and data querying languages for data manipulation and analysis. Proficiency in Azure Data Factory and DBT, with a demonstrated ability to build scalable and reliable data pipelines and transformation processes.
  • Familiarity with data modelling concepts and techniques, including dimensional modelling.
  • Strong problem-solving and analytical skills, with the ability to analyse complex data-related issues and provide effective solutions.
  • Excellent communication and collaboration skills, with the ability to work effectively in a team environment and engage with stakeholders at various levels.

Please note that all applying applicants should already have a Right to Work in the UK status in place and have a number of years relevant industry experience behind them to meet the important requirements of this role.

WEG Technology is acting as an internal recruitment agency

Please send your CV with a Cover Letter to Pete.Hampshire@warwick.ac.uk

This job was originally posted as: https://thecareerwallet.com/stats/track/MTUyNzUyNTc5NC18LTE0NS18LTcw

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