Job Purpose
The Head of Data Engineering and Architecture will lead the Data Engineering team in developing and supporting a University-wide resilient, trusted data platform, underpinning the University's goals of delivering insight and intelligence across the institution.
The post holder will be accountable for establishing data architecture/engineering principles, standards and design patterns, delivering data engineering improvements in line with modern best practice, and directing and managing the work of the data engineering team.
The post holder will work closely with the data governance, data analytics and strategic planning teams in Planning, Insight and Analytics, and with specialist data, technology and enterprise architecture colleagues across University Services, particularly in Information Services.
Main Duties and Responsibilities
1. To lead the data engineering team, organise resource to match delivery and ensure that the team are supported to deliver fully and achieve their full development and skills potential.
2. Personally lead and deliver a range of university-wide data engineering improvement initiatives, including the evolution of the data warehouse into a trusted data platform for the wider university, and lead on projects involving multifunctional teams. Report as required to relevant Project Boards on all aspects of the management and delivery of these projects, preparing and delivering high-quality reports and presentations as required.
3. Drive action and engagement across the University to ensure the successful delivery and adoption of the trusted data platform and other innovative changes, in partnership with other services.
4. Create and build strong, mutually beneficial relationships with key stakeholders, providing a recognised and important bridge between PIA and University Services, to ensure there is alignment between the wider work of the Directorate, the Colleges and Service Heads.
5. Develop the University's data architecture and modelling capability to ensure that all solutions conform to data engineering standards, architecture principles and design patterns.
6. Contribute as a member of the University's Enterprise Design Authority, ensuring technology proposals are reviewed thoroughly but pragmatically from a data perspective.
7. To plan for the future needs of the team by ensuring that skills and training are regularly reviewed and updated in the context of strategic business objectives and with a strong focus on continuous professional development.
8. Identify opportunities for efficiency improvements, innovations, and new data sources which will benefit the University.
9. Horizon scan to stay up to date with the latest technology, techniques and methods so as to advance the work of the team.
10. Act as the contact point for ensuring work is distributed across the wider engineering team.
11. Represent the team at meetings, external groups/conferences and seminars to keep up to date with national developments and gain information/knowledge of working practices in the higher education context.
12. Support the development of the PIA business plan and lead on ongoing improvement and development to continuously enhance service effectiveness and reputation.
13. Play a key role in the management of the Directorate including investing in the development and capabilities of our staff, and in supporting a positive and inclusive work culture.
14. Contribute to the effective cross-service management of the Planning, Insight and Analytics service including deputising for the Chief Data Officer where appropriate.
Knowledge, Qualifications, Skills and Experience
Knowledge/Qualifications
Essential:
A1 Ability to demonstrate the competencies required to undertake the duties associated with this level of post having acquired the necessary professional knowledge and management skills in a similar or number of different specialist roles. Or: Scottish Credit and Qualification Framework level 9, 10 or 11 (Ordinary/Honours Degree, Post Graduate Qualification), or equivalent, including being professionally qualified in relevant discipline, with a broad range of professional experience in a management role(s).
A2 Detailed knowledge of the concepts and principles of data modelling and data architecture diagramming practices.
A3 An understanding of the fundamental stages of the agile data analytics delivery lifecycle including ETL and data cleansing skills, data modelling and architecture, code management and version control.
A4 Detailed knowledge of enterprise-scale data integration approaches and tools.
A5 Detailed knowledge of relational database management systems and SQL, preferably Oracle.
A6 Detailed knowledge of data-centric programming languages e.g., PL/SQL, Python, JavaScript, Java.
Desirable:
B1 Scrum certification or PRINCE2 Practitioner certificate.
B2 Knowledge of Agile project management methodologies.
B3 Knowledge of business intelligence tools such as Power BI, Tableau, QlikSense.
B4 Knowledge of data integration tools, such as Qlik Data Integration, Talend, Matillion, Informatica, Azure Data Factory.
B5 Exposure to Enterprise Architecture either generically, or via a specific framework such as TOGAF
B6 Knowledge of project management tools such as ClickUp, JIRA, Trello, Azure DevOps.
B7 Awareness of the Higher Education environment.
B8 Knowledge of a range of data management paradigms, such as data mesh, data vault, star/snowflake schema and third normal form.
Skills
Essential: C1 Excellent interpersonal, organisational and communication skills with the ability to succinctly translate complex information to non- specialists.
C2 Drive, enthusiasm, with a high degree of personal effectiveness and professional credibility focussed on achieving good business outcomes.
C3 Ability to write detailed project plans and ensure these are agreed and communicated with the project team, project board and stakeholders.
C4 Ability to understand and apply data modelling techniques and produce relevant data models.
C5 Understand and can help teams apply a range of techniques for data profiling and building conformed data models
C6 Establish standards and keep those standards up to date and ensure adherence to them.
C7 Excellent analytical and problem-solving skills, with the ability to bridge the gap between technical and non-technical.
C8 The ability to engage and positively manage relationships with those delivering and impacted by change.
C9 Able to listen to the needs of technical and business stakeholders and interpret them. Facilitate difficult discussions within the team or with diverse senior stakeholders.
C10 Proven ability to liaise and communicate effectively in a concise and confident manner with the ability to persuade and influence a range of individuals/groups across organisational boundaries.
C11 Strong leadership and motivational skills.
C12 Effective written and communication skills to produce clear project management documents and sponsor and stakeholder focused content.
Experience
Essential: E1 Extensive hands-on experience in creating data models and ETL/ELT pipelines for analytics applications.
E2 Extensive experience with integration of data from multiple sources.
E3 Significant experience of data warehouse design patterns and best practice.
E4 Experience with version control and code management tools e.g. Git, GitHub, Gitlab.
E5 Experience in designing and helping to build resilient and reliable data processes and culture.
E6 Extensive experience of collaborating with and influencing senior leaders across organisational boundaries to reach consensus and an agreed outcome.
E7 Extensive experience of managing complex projects with strategic influence, with significant impact upon resources.
E8 Extensive experience of report writing and producing project documentation.
E9 Significant experience of developing innovative solutions and contributing to strategic planning.
E10 Substantial expertise in leading business analysis and formulating recommendations for change.
Desirable :
F1 Experience of supporting and developing business intelligence systems and data visualisation tools such as Power BI, Tableau and Qlik Sense.
F2 Experience of using cloud-based data engineering and orchestration tools, such as Airflow, Dagster, dbt, FiveTran, Prefect.
F3 Experience of using cloud-based data cataloguing and quality tools, such as DataHub, Purview, Great Expectations.
F4 Experience of using and developing continuous integration/continuous deployment practices in software development or data workflows.
This is a full time (35 hours per week), open ended role (permanent).
As part of Team UofG you will be a member of a world changing, inclusive community, which values ambition, excellence, integrity and curiosity.
As a valued member of our team, you can expect:
1 A warm welcoming and engaging organisational culture, where your talents are developed and nurtured, and success is celebrated and shared.
2 An excellent employment package with generous terms and conditions including 41 days of leave for full time staff, pension, benefits and discount packages.
3 A flexible approach to working.
4 A commitment to support your health and wellbeing
We believe that we can only reach our full potential through the talents of all. Equality, diversity and inclusion are at the heart of our values. Applications are particularly welcome from across our communities and in particular people from the Black, Asian and Minority Ethnic (BAME) community, and other protected characteristics who are under-represented within the University. Read more on how the University promotes and embeds all aspects of equality and diversity within our community here
We endorse the principles of Athena Swan and hold bronze, silver and gold awards across the University.
We are investing in our organisation, and we will invest in you too. Please visit our website https: // www. gla.ac.uk/explore/jobs/for more information.
Vacancy Ref : 135615 Close Date : 26-Feb-2024 23:45