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For Companies At a Glance
- Tasks: Analyse large-scale movement datasets to generate insights on audience behaviour.
- Company: Join a leading organisation in Out-of-Home advertising measurement.
- Benefits: Enjoy flexible working with 2-3 days in the office and competitive salary.
- Why this job: Be part of a small, technical team making impactful media decisions through data.
- Qualifications: Experience with spatial data, SQL, and tools like Tableau is essential.
- Other info: Ideal for those passionate about geospatial analysis and audience insights.
The predicted salary is between 34000 - 42000 £ per year.
Job Description
FinOps Data Analyst
Up to £47,000 | Leicester | Hybrid (4 days onsite)
About the Role
We're working with a major UK retail brand to hire a FinOps Data Analyst for their Finance Analytics team. You'll provide analytical support and reporting solutions across multiple finance functions, working closely with SQL engineers and Finance stakeholders.
This hands-on role uses SQL and Python daily to explore data, identify trends, and deliver actionable insights that drive financial decision-making. The team is modernising their data platform with Databricks and Medallion Architecture, giving you exposure to cutting-edge technologies.
Key Responsibilities
- Build analytical solutions and reporting across 4 finance areas: Accounts Payable, Cash Accounting, Commercial Services, and Operations.
- Perform SQL-based data exploration, validation, and transformation.
- Use Python (Pandas/Numpy) for analysis, automation, and data profiling.
- Build Power BI dashboards to visualise financial metrics.
- Support ad-hoc analysis by exploring trends and anomalies.
- Engage with stakeholders to gather requirements and deliver analytical outputs.
- Contribute to self-service analytics and data literacy initiatives.
Current Projects
- Databricks Modernisation: Exposure to Databricks as the team builds Gold Standard Medallion Architecture.
- Self-Service Analytics: Reducing ad-hoc queries (currently 60-70% of workload) by building reusable assets.
- BAU Finance Support: Ongoing analytics across AP, Cash Accounting, Commercial Services, and Operations.
- Analytical Automation: Using Python/SQL to streamline recurring finance analysis.
- Future ML/AI: The team will explore machine learning applications in finance analytics.
Requirements
Essential:
- Strong SQL (querying, joins, CTEs, window functions, data profiling).
- Python for data analysis (Pandas, Numpy).
- Power BI experience (dashboard creation, no heavy DAX required).
- Strong analytical mindset and communication skills.
- Onsite presence: Able to work in Leicester 4 days/week (5 days for the first 3 months).
Desirable:
- Databricks or modern cloud data platforms.
- Experience within a Finance team or working with financial data.
- Data warehousing knowledge.
What You'll Get
- Salary up to £47,000.
- Exposure to modern data tech (Databricks, Medallion Architecture).
- ML/AI exposure as the team evolves.
- Hybrid working (4 days onsite after initial training).
- Career development in a major UK retailer.
Interview Process
- Stage 1: Informal discussion with Analytics Manager (45 mins, virtual).
- Stage 2: In-person assessment (3 hours total).
- 2 hours: Analytical task using SQL/Python on a provided dataset.
- 1 hour: Discussion reviewing your approach and reasoning.
Working Arrangements
- First 3 months: 5 days/week onsite for training.
- After 3 months: 4 days/week onsite, 1 day remote.
This is a fantastic opportunity for a Data Analyst looking to specialise in Finance analytics while developing skills in modern data platforms and ML/AI.
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Familiarise yourself with the latest trends in spatial data analysis and geospatial techniques. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the media and advertising sectors, especially those who work with location intelligence. Attend industry events or webinars to make connections that could lead to valuable insights or referrals.
✨Tip Number 3
Brush up on your SQL skills by working on real-world datasets. Consider creating a portfolio of projects that showcase your ability to query complex data and generate insights, as this can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss specific examples of how you've used tools like Tableau or BigQuery GIS in past projects. Being able to articulate your experience with these tools will demonstrate your readiness for the role.
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with spatial data and geospatial techniques. Include specific examples of projects where you've used SQL for complex data querying and any relevant tools like Tableau or BigQuery GIS.
Craft a Compelling Cover Letter: In your cover letter, express your passion for audience measurement in Out-of-Home advertising. Discuss how your skills align with the role's requirements, particularly your experience in analysing movement datasets and producing visualisations.
Showcase Relevant Projects: If you have worked on projects involving location-based data analysis or audience behaviour insights, summarise these in your application. Highlight the methodologies you used and the impact of your findings.
Proofread Your Application: Before submitting, carefully proofread your application to ensure there are no typos or grammatical errors. A polished application reflects your attention to detail, which is crucial for a Data Analyst role.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with spatial data and geospatial techniques. Highlight specific projects where you used SQL for complex data querying and how you applied these skills to derive insights.
✨Demonstrate Your Analytical Mindset
During the interview, share examples of how you've approached problem-solving in past roles. Discuss your curiosity and passion for unlocking insights from movement data, as this aligns with the company's focus on audience behaviour.
✨Familiarise Yourself with Relevant Tools
Make sure you are well-versed in tools like Tableau, BigQuery GIS, or PostGIS. Be ready to explain how you've used these tools in previous roles to create visualisations or perform geospatial analysis.
✨Prepare Questions About the Company
Research the organisation's role in the OOH advertising sector and prepare insightful questions. This shows your genuine interest in the company and helps you understand how you can contribute to their goals.
