Junior BI Analyst

Location: London – various locations. Salary: Competitive salary plus a generous benefits package. Application Deadline: Friday, June 5, 2026.

Job Summary

We are looking for a Junior BI Analyst to join our Data team and help build the firm’s modern data foundation. You'll contribute to the design and delivery of our data strategy by helping the business harness data to understand client and prospect behaviour, preferences, and interactions, supporting activity to capture, grow and retain higher client value and drive ROI. The role will support the unification of on‑premises and cloud data sources into trusted reporting and analytical outputs, helping to collect, validate, analyse and visualise data through dashboards and reusable datasets, while developing the foundations for modern analytics, AI and machine learning applications. This is an early‑career role suited to a highly motivated analyst with strong technical aptitude, relevant internship, placement or project experience, and the confidence to work with SQL and, ideally, Python. The successful candidate will work closely with senior analysts, data engineering and business stakeholders, taking ownership of defined pieces of analysis and reporting while continuing to develop deeper BI and data‑platform expertise.

Key Accountabilities

• Modernising data and reporting – servicing tickets and month‑end reports
• Deliver regular reports, dashboards and decision‑ready outputs on time, applying strong quality checks for accuracy, consistency and completeness.
• Respond to reporting requests and data tickets, clarifying requirements and escalating complexity where appropriate.
• Develop knowledge of business data, reporting logic and client‑related metrics to support wider analysis and insight.
• Contribute to continuous improvement in data and reporting by identifying recurring issues, reducing manual effort and improving scalability.
• Support automation and modernisation activity, including migration of suitable reporting into self‑serve solutions using Power BI and Databricks.

Contributing to a Modern Data Platform on Databricks

• Work with Data Engineering, analysts and stakeholders to understand how Databricks is used for analytics and BI, and contribute to defined delivery tasks.
• Translate business questions into clear analytical requirements with support from senior colleagues, including basic data model and semantic‑layer considerations.
• Help challenge legacy reporting patterns by documenting current processes, identifying improvement opportunities and applying agreed analytics standards.
• Support the move towards self‑service analytics and reusable datasets, reducing reliance on bespoke reporting where appropriate.

Modelling, Metrics & Data Quality

• Support the definition and stewardship of core business metrics, ensuring definitions, assumptions and logic are documented, clear and consistently applied.
• Build and maintain analytics‑ready datasets and reporting outputs under guidance, using SQL confidently and Python where appropriate.
• Monitor metric behaviour over time, helping to investigate drift, anomalies and inconsistencies and coordinating resolution with relevant teams.
• Help ensure consistency between legacy and Databricks‑based reporting during the transition.

Insight & Decision Support

• Analyse and interpret key metrics to explain trends, changes and performance drivers.
• Provide clear narrative and context to support decision‑making, focusing on why results have changed rather than simply reporting the numbers.
• Support exploratory analysis, scenario testing and "what changed" investigations for stakeholders.
• Identify limitations in current data, models or reporting and explain what would be required to improve insight.

Competencies/Skills Set

• Strong analytical and problem‑solving ability, with confidence working with data and the potential to work with larger, more complex datasets.
• Ability to identify what matters, ask insightful questions and cut through noise in analysis.
• High attention to detail, particularly around data quality, reconciliations and metric consistency.
• Ability to prioritise and deliver in a fast‑moving environment, balancing BAU reporting with improvement work.
• Curious, inquisitive mindset with a strong interest in client experience, service design and commercial outcomes.

• Understanding of analytical data models, reporting logic and how metrics are defined and used in decision‑making.
• Ability to document definitions, assumptions and logic clearly, and to spot inconsistencies or unexpected changes in metrics.
• Motivation to develop robust modelling and metric‑stewardship skills through practical delivery and coaching.

• Clear and confident communicator with both technical and non‑technical audiences.
• Able to gather requirements, clarify questions and explain analytical findings in a concise, structured way.
• Collaborative team player who shares knowledge, seeks feedback and supports colleagues.

• Confident SQL skills, including joins, aggregations, filtering, data validation and writing queries to support analysis and reporting.
• Python capability is highly desirable, particularly for data exploration, analysis, automation or prototyping.
• Experience with modern BI tools and dashboard design, ideally Power BI, through work, internships, placements, academic projects or self‑directed projects.
• Exposure to Databricks or cloud data platforms is desirable, but can be developed in role.
• Strong Excel skills for analysis, checking, reconciliation and communication of results.

• 0–2 years’ professional experience in analytics, business intelligence, reporting, data, finance, operations or a similar environment; relevant internships, industrial placements, graduate placements or substantial project experience are highly valued.
• A degree in a relevant discipline such as data science, statistics, mathematics, analytics, economics, computer science or another quantitative field, or equivalent practical experience, is desirable.
• Demonstrable motivation to build a career in BI and analytics, evidenced through internships, placements, projects, portfolios, coursework, certifications or self‑directed learning.
• Confident use of SQL to analyse data, investigate issues and support reporting; candidates should be comfortable writing queries rather than relying solely on pre‑built reports.
• Python experience is highly desirable for analysis, data exploration, automation or prototyping analytical solutions.
• Experience with a modern BI and visualisation tool, ideally Power BI, is desirable; strong candidates may evidence this through internships, placements, academic work or personal projects.