Data Analyst (Customer & Sales)
The BrandAlley Group
- London, England, United Kingdom
- London, England, United Kingdom
About
Salary: Up to £40,000 per annum
Location: London (Hybrid – 3 days per week in the London office)
Experience level: Couple of years' relevant analytics experience
Reporting to: Lead Analyst/Analytics Manager
Key partners: Data Engineer, Trading, Marketing, Finance, Operations, Fulfilment
BrandAlley is seeking a Data Analyst to support performance reporting and commercial insights across our e-commerce business. This role will work closely with the Lead Analyst/Analytics Manager and our Data Engineer to ensure stakeholders have a clear, trusted view of customer and sales performance. You will work primarily in
Lightdash
and
Excel , maintaining and improving dashboards and recurring reporting. While the majority of reporting is already available in Lightdash, you will occasionally use
SQL (Snowflake)
for ad-hoc requests where data is not yet modelled and collaborate with the Data Engineer to bring repeatable requirements into Lightdash over time.
Key Responsibilities
Maintain and enhance reporting in Lightdash, ensuring dashboards are accurate, well-structured, and easy for teams to use
Produce analysis in Excel to support weekly reporting and deep dives (structured tables, pivots, reconciliations, charts, and concise written commentary)
Analyse customer and sales data (orders, customers, refunds/returns) to identify trends and performance drivers, including retention/churn, conversion funnel metrics, AOV, and trading KPIs
Support the weekly performance cadence by preparing accurate inputs and insight commentary for senior stakeholders
Respond to ad-hoc requests across Trading and Marketing, translating business questions into clear outputs and recommendations
Use SQL in Snowflake when required to extract datasets and validate reporting where data is not yet available in Lightdash
Work closely with the Data Engineer to define requirements (metric definitions, grain, source logic), helping to operationalise recurring requests into Lightdash
Apply strong Quality Assurance and documentation practices to ensure outputs are reliable and assumptions are understood
Required Skills And Experience
A couple of years in an analytics role, ideally within e-commerce or retail, working with customer and sales data
Strong proficiency in Excel, including pivot tables, formulas, charting, and producing structured, presentable outputs
Experience working with customer and sales datasets (orders, customers, refunds/returns, retention/cohort concepts)
Demonstrable dashboarding capability using Tableau and/or Power BI (Lightdash experience is not required; we value strong dashboard fundamentals)
Working knowledge of SQL for analytics, including joins, aggregations and CTEs, sufficient to support occasional ad‑hoc querying and extraction from Snowflake
Strong attention to detail, with a clear approach to Quality Assurance, reconciliation, and communicating assumptions
Confident communication skills and the ability to work effectively with non-technical stakeholders
Desirable Skills
Familiarity with Google Analytics4 (GA4) and digital performance metrics (traffic, engagement, conversion, attribution considerations)
Commercial awareness of core trading metrics (gross vs net sales, returns rate, margin fundamentals)
Experience working alongside data engineering teams and contributing to metric definitions and documentation
What Success Looks Like (First 90 Days)
Independently deliver accurate recurring outputs and analysis using Lightdash + Excel, with strong Quality Assurance checks.
Build or improve at least one dashboard/reporting flow to increase clarity, usability, or confidence in the numbers.
Handle ad‑hoc requests end-to-end, using SQL when necessary and collaborating with the Data Engineer to productionise repeatable needs.
Working Pattern This is a hybrid role requiring three days per week in our East London office.
Seniority Level Not Applicable
Employment Type Full-time
Job Function Information Technology
Industries Retail
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Languages
- English
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