Data & Privacy Risk Specialist Manager in Bristol

Requirements

• You’ll bring hands‑on data fluency, the ability to validate technical logic, and confidence in challenging engineering and analytical teams.
• A strong practical understanding of the full data lifecycle – from collection, use and transformation through to retention and deletion – is important, along with an interest in how emerging technologies such as AI influence data use, governance and risk.
• Regulatory and risk knowledge (e.g., GDPR, operational risk concepts) is desirable, but we expect this expertise to grow rapidly in role.
• You’ll thrive if you enjoy:
• Applying practical data expertise to real-world oversight challenges.
• Bringing precision, structure and clarity to complex assessments.
• Using analytics to shape how risk is understood and evidenced.
• Turning regulatory requirements into measurable, data‑driven outcomes.
• Hands‑on understanding of data lifecycles: collection, use, ingestion, transformation, storage, access, retention and deletion.
• Ability to read, interpret and challenge code (e.g., SQL, Python) and assess analytical logic.
• Experience with data modelling, pipelines, extract, transform, load concepts and working with engineering teams.
• Proficiency with analytical tools (SQL, Python, Power BI, Tableau).
• Ability to build automated or reproducible analytical outputs.
• Understanding of metadata, data architecture concepts or AI/ML fundamentals.
• Confident operating as the analytical lead within a senior team.
• Able to independently influence and challenge constructively.
• Strong communication skills, with the ability to simplify complex analytical or technical issues.
• (Desirable) Understanding of risk management, compliance or operational risk.
• (Desirable) Interest in developing strong knowledge of data privacy, the Data Use Act, emerging digital and data laws, and the wider regulatory frameworks that impact how data is handled.
• (Desirable) Demonstrated ability to learn complex theoretical frameworks quickly and apply them pragmatically.
• (Desirable) Familiarity with data protection principles (e.g., personal data, minimisation, retention).
• (Desirable) Exposure to DPIAs, privacy‑by‑design or related governance practices.
• (Desirable) Awareness of recordkeeping standards, retention schedules or legal hold processes.

What the job involves

We’re looking for a highly skilled analytical specialist to lead the data‑driven oversight approach within the Data Privacy, Retention & Records Management Risk team. This role will shape how we use analytics, metrics and data‑lifecycle‑based evaluation – including emerging AI‑enabled techniques – to oversee data management risks across the organisation.

Working closely with Senior Managers and the Head of Function, you’ll define the analytical methods, tools and measurement techniques that underpin our oversight model.

• Lead development of a precision‑driven, analytics‑based oversight model for data privacy, retention and records risks.
• Translate oversight questions into measurable indicators, diagnostics, and metrics.
• Identify process weaknesses, control gaps and emerging risks using robust analytical methods.
• Build reproducible reports, dashboards and analytical tools that deliver consistent, evidence‑based oversight.

Lifecycle‑Informed Oversight & Data‑Driven Methods

• Apply deep understanding of data lifecycles to assess how controls operate in real systems and processes.
• Translate regulatory and policy requirements into measurable, testable, evidence‑backed controls.
• Evaluate control maturity and effectiveness through precise, data‑accurate techniques.
• Conduct oversight across:
• Data Privacy Impact Assessment pipeline performance and thematic assessment.
• Retention and deletion controls.
• Records classification and maintenance.
• Metadata, lineage and lifecycle verification.
• Develop oversight routines focused on clarity, repeatability and high‑quality evidence.
• Partner with engineering, platform and architecture teams to ensure analytical methods and evidence genuinely enable effective challenge.
• Provide structured challenge and insight on data privacy, retention and records‑related risks.
• Produce high‑quality oversight outputs, including reports, summaries and committee materials.
• Support incidents and issues using a data‑driven diagnostic mindset.
• Apply developing regulatory and risk knowledge to contextualise findings.
• Work across Risk, Legal, Engineering, Data Architecture and Operations teams.
• Communicate analytical findings in clear, accessible language.
• Act as the lead for the team, improving analytical maturity and embedding a precision‑led oversight culture.