Job Description

Data Analyst (Customer & Sales)

BrandAlley

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

(our BI tool) 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