At a Glance
- Tasks: Lead data quality improvements and ensure data accuracy across the organisation.
- Company: Join St. James's Place, an inclusive employer committed to diversity.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on innovation and collaboration.
- Why this job: Make a real impact by enhancing data quality and supporting better decision-making.
- Qualifications: Passion for data, strong analytical skills, and stakeholder engagement experience.
The predicted salary is between 37800 - 46200 £ per year.
This job is with St. James's Place, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community.
The Data Quality Analyst sits within the DALQS (Data Acquisition, Literacy, Quality & Strategy) function, now combined with Data Governance & Intelligence (DG&I), within SJP's wider Data & Insights division. The division is structured across three core verticals:
- Data acquisition, quality, governance, literacy and strategy
- Data architecture, platforms and engineering
- Data Insights - Business-led reporting and visualisation
The role is non-managerial, operating within a matrix structure and working closely with:
- Data Acquisition, Governance and Strategy teams
- Engineering and platform teams
- Business and reporting stakeholders
Data Quality acts as an upstream, business-facing function, connecting external data providers with internal data, technology and business teams.
What you'll be doing:
Reporting to the Data Quality Lead in the Data Acquisition, Quality, & Strategy division of the Data & Insights (D&I) team, the role holder will be responsible for owning and leading the identification, definition and delivery of enterprise data quality (DQ) improvements across SJP, acting as a key interface between business domains and technical teams. The role is responsible for driving proactive, value-led DQ management embedded within business processes and data products, ensuring data is trusted, fit-for-purpose and aligned to SJP's strategic objectives.
Who we're looking for:
A data enthusiast, passionate about data accuracy, consistency, validity, integrity, and the value that excellent data delivers to the organisation. We're looking for individuals who bring a business-first approach, always thinking about outcomes, impact, and how data enables better decision-making across the organisation.
Key responsibilities:
- Own and lead the delivery of Data Quality improvement outcomes across assigned business domains or data products, ensuring alignment to business value, client impact, and risk reduction priorities.
- Proactively identify and prioritise risks and opportunities, using data insight, profiling and stakeholder engagement to focus on areas of the highest impact to SJP.
- Support, and where required lead, root cause analysis of complex issues, ensuring remediation addresses systemic causes and drives sustainable, preventative improvement.
- Support the design, development and ongoing operation of controls, monitoring and reporting solutions, ensuring technical implementations remain aligned to business needs and enterprise Data Quality standards.
- Hold Data Owners and Data Stewards to account for outcomes, ensuring clear ownership, prioritisation and timely resolution of issues in line with agreed standards.
- Coordinate cross-functional remediation and prevention activities, working with business stakeholders, Data Stewards and technical teams to deliver measurable and sustained improvements.
- Providing guidance, challenge and support to business domains to embed DQ within processes, controls and data products.
- Enable the business to monitor and manage its own DQ, by defining and interpreting meaningful metrics, dashboards and insights that support decision-making and accountability.
- Define business requirements for controls and partner with technical teams to ensure solutions are scalable, consistent and aligned to SJP standards and architecture.
Essential Criteria:
- Strong understanding of Data Quality frameworks and best practice, with the ability to apply these in a practical, outcome-focused way.
- Experience working within data-led operating models (e.g. data domains, data products, value streams).
- Ability to prioritise Data Quality activities based on business impact and risk.
- Strong stakeholder engagement skills, with the ability to build relationships and challenge constructively.
- Demonstrated ability to translate business problems into structured data quality requirements.
- Self-motivated and able to manage workload independently, driving work forward without close supervision.
- Strong analytical and problem-solving skills, with the ability to bring clarity to complex or ambiguous issues.
- Working knowledge of data tools and techniques (e.g. SQL, Power BI, Snowflake, Aperture), with a focus on understanding rather than deep technical development.
Desirable Criteria:
- Wealth Management experience.
Data Quality Analyst employer: St. James's Place
St. James’s Place is an excellent employer, offering a dynamic work culture that prioritises employee well-being and professional growth. Located in Cirencester, this hybrid role as a Data Privacy Manager not only provides competitive benefits such as parental leave and health insurance but also fosters an environment where employees can thrive through collaboration and engagement with diverse stakeholders in the regulated financial services sector.
StudySmarter Expert Advice🤫
We think this is how you could land Data Quality Analyst
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We think you need these skills to ace Data Quality Analyst
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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How to prepare for a job interview at St. James's Place
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at St. James's Place!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
