Data Analyst

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.

Key Responsibilities Build analytical solutions 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 analysis by exploring trends and anomalies. Engage with stakeholders to gather requirements and deliver analytical outputs.

Current Projects Databricks Modernisation: Exposure to Databricks as the team builds Gold Standard Medallion Architecture. Self-Service Analytics: Reducing queries (currently 60-70% of workload). BAU Finance Support: Ongoing analytics across AP, Cash, Commercial Services, Operations. Analytical Automation: Using Python/SQL to streamline recurring analysis. Future ML/AI: The team will explore machine learning applications.

Requirements Essential: Strong SQL (querying, joins, CTEs, window functions). Python for data analysis (Pandas, Numpy). Power BI experience (dashboard creation). Strong analytical mindset and communication skills. Able to work onsite in Leicester 4 days/week (5 days first 3 months).

Desirable: Databricks or modern cloud data platforms. Finance team or financial data experience. Data warehousing knowledge.

What You'll Get Salary up to £47,000. Modern data tech (Databricks, Medallion Architecture). ML/AI exposure as team evolves. Hybrid working (4 days onsite after training). Career development in 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 provided dataset, 1 hour discussion reviewing your approach.

Working Arrangements First 3 months: 5 days/week onsite for training. After 3 months: 4 days/week onsite, 1 day remote.

To apply, submit your CV or contact us for more information.