Duties and Responsibilities The Head of Business Intelligence (BI) and Data Analytics (DA) is responsible for the Authoritys data strategy, providing leadership, trusted advice and practical experience in delivering Business Intelligence and Data Analytics solutions.
The Head of Business Intelligence and Data Analytics will be required to meet challenging goals in an innovative but controlled manner, and to assist the NTA in the next phase of its data journey.
Key Accountabilities: Data Analytics Strategy: Implement, refine and adapt the Data Analytics Strategy to assist the NTA to achieve its organisational goals and elevate the NTAs data capability to meet the needs of internal and external stakeholders; Resource planning, budgeting, and team management of the Business Intelligence and Data Analytics team; Maintain the data analytics roadmap, adapting it to the changing needs of the organisation; Implementing the data-related components of NTAs artificial intelligence (AI) Strategy roadmap; Manage the NTAs strategic data assets to extract the maximum value and meet the NTAs internal and external data obligations; and Vendor management and service procurement complying with public sector guidelines; Data Analytics (DA) Development and Delivery: Identify data acquisition opportunities, and implement the associated data acquisition processes in line with NTA strategy; Manage data storage solutions and compliance of these solutions with the NTA data security and data protection policies; Manage data asset integration in a cloud-based Enterprise Data Warehouse environment utilising analytics tools such as Microsoft Fabric, Azure Synapse and Azure Data Factory; Apply data analytics techniques such as machine learning and artificial intelligence, including GenAI, as well as traditional data analysis techniques, leveraging data programming tools such as Python, R and SQL; Ensure the NTAs artificial intelligence Centre of Excellence is resourced with the requisite data science skills to turn Proof of Concepts into products; Deploy data presentation solutions that incorporate visualisation techniques that are appropriate to the business needs utilising tools such as Power BI; and Deliver a hub and spoke self-service analytics operating model across the NTA.
Data Management: Implement a data governance programme within the NTA, bring about the required organisational change, implementing the required boards and committees and leveraging leading edge data cataloguing software; Integrate new sources of batch and near real-time data from the NTAs various systems (e.g.
next generation ticketing systems, automated-vehicle-location (AVL) systems, real-time GTFS) into the NTA data platform, to provide a single view of passenger journeys; Rollout DAs automated Enterprise Data Warehouse across all new and existing data sources; Enhancing the NTA data platform with external third-party data sources such as geospatial and mobile data; Optimise the data-sharing potential of the NTA data platform with external stakeholders while meeting GDPR obligations; and Implement a Master Data Management system and associated controls in line with best practice.
Data Analytics Architecture and Standards: Oversee and approve Data Analytics architectural solutions and work with the architecture team to ensure that the solutions are in line with the NTA architectural guidelines; and Implement and continuously review and improve development standards, solution design standards, data access standards and Data Analytics platform standards.
Managed Data Services (MDS): Work with the external MDS vendor to provide support that meets the needs of the user; Refine and implement support procedures to cover existing and new systems that Business Intelligence and Data Analytics have responsibility for; and Manage Service Level Agreements and make improvements where necessary to ensure the Service Level Agreement targets are met.
Key Challenges: Innovating to fulfil expanding Business Intelligence and Data Analytics demands in a timely and controlled manner; Meeting business needs with a constrained Data Analytics resource.
Eliciting engagement with business units that have limited capacity; and Managing teams and vendor relationships in a multi-vendor environment.
Note:The functions and responsibilities initially assigned to the position are based on the current organisational requirements and may be changed from time to time.
The person appointed requires the flexibility to fulfil other roles and responsibilities at a similar level within the Authority.
Essential Criteria Please note: In order to satisfy the shortlisting panel that you meet these criteria you must explicitly reference how you meet same in your application.
Failure to demonstrate these may prevent your application progressing to future shortlisting stages.
Each candidate must meet the following requirements at the time of the competition closing: Hold a minimum of a NFQ Level 8 qualification in Data Management, Innovation, Data Analytics or a relevant business related discipline; At least 5 years of experience working within a Business Intelligence and Data Analytics management role, demonstrating the ability to add value to the organisation; At least 2 years of experience in managing implementations in the Azure Business Intelligence stack including Azure Data Lake, Azure Data Warehouse, Azure Data Factory, Power BI etc.
; At least 2 years of experience in delivering cloud-based machine learning and / or artificial intelligence solutions; The ability to build strong trust relationships with key stakeholders, to create Business Intelligence and Data Analytics champions and provide advice to C-Suite; Strong communication, interpersonal and influencing skills with challenging senior stakeholders; and Excellent decision-making, problem-solving, organisational, and time-management skills.
Desirable Criteria Please note: Should further shortlisting be required after essential criteria above, a selection of the following may be assessed.
The ideal candidate will also: A minimum of a NFQ Level 9 in Data Management, Innovation, Data Analytics or a relevant business related discipline; Good knowledge of public transport technology initiatives and of trends in Business Intelligence and Data Analytics technology; A working knowledge of key technical components of the Data Analytics environment; A good understanding of Agile development frameworks; Strong team management, preferably in a multi-vendor environment.
Experience in managing offshore resources an advantage; A working knowledge of SQL; Ability to juggle different projects/priorities and deliver high quality outcomes under pressure; and Strong motivation and ability to work with minimal supervision and direction.
Skills: Identifies coherent solutions to complex issues Develops a culture of learning & development Maintains a strong focus on self-development