Job Purpose :

The key purpose of this role is to define desirable, viable, feasible, and sustainable data solutions that meet organisational needs for ubiquitous timely and accurate information and to support development across the product life cycle.

The role is a key conduit between the business stakeholders and the lab development teams, engineers and other domain services and maintains alignment with the Product Owner's vision and goals and the prioritised backlog.

Core Responsibilities :

- Partner the Data Product Owner, Engineers, QA's and product team in identifying product improvement opportunities in line with business Outcomes and Key Results (OKRs), the Product Owner's vision and roadmap.

- Lead complex business analysis across multiple stakeholders and business functions, while providing line management for a team of Business Analysts, including mentoring, coaching, performance management, setting objectives and conducting regular 1-2-1s.

- Define and standardise best practice for data analysis, requirements gathering and documentation to improve consistency and quality across the BA data function.

- Act as a key liaison between business stakeholders, product owners and development team in an Agile environment, ensuring clear communication and alignment of business objectives.

- Conduct business impact assessments, feasibility studies and research into systems, processes and products as required, making recommendations for the best options available to meet business objectives.

- Support the Product Owner in prioritising the backlog and backlog items based on business value and delivery constraints and dependencies.

- Responsible for requirement elicitation and analysis for the prioritised backlog within agreed timelines, decomposing into functional and technical user stories and ensuring that they are clear, concise, actionable and testable.

- Develop data models, data flows and other data related artefacts to visualise data relationship and process.

- Assure solutions through techniques such as data modelling, data lineage, data dictionary, and information quality requirements.

- Assure the quality of analysis artefacts building-in quality through a range of techniques including peer and expert review, upholding artefact standards, maintaining tool-based trace, and applying fail-fast build and learn techniques.

- Actively participate in all relevant Agile events such as PI planning, backlog refinement and retrospectives advocating for alignment and relentless improvement.

- Represent Lab as Subject Matter Expert with a working knowledge of the organisation's domain: its services, technologies, architecture, business processes and procedures.

- Ensure that you fully understand and comply with the organisation's Risk Management and Data Governance Policies.