This repository documents the interview process I built this week for a Senior Ecommerce Data Analyst role. Created with the hiring team, it outlines a structured, multi-stage approach covering technical skills, stakeholder collaboration, and cultural fit.
Over the past week, I’ve been working with a hiring team to design and agree an interview process for a Senior Ecommerce Data Analyst role.
The aim was to create a structured, fair process that balances technical assessment, stakeholder experience, and cultural alignment, while respecting candidate time. We aligned on a multi-stage approach (3 stages with a take home challenge), outlined below.
This repository provides a public, high-level overview of that process to help candidates understand what to expect.
Stage 1 — Technical Take-Home Challenge (Av. time to complete (based off of 19 candidate submissions = 25 minutes) (candidates have 5 days to submit their challenge)
Format
- SQL-focused take-home challenge via Codility platform (ex. level red 'hard')
Purpose
Assess core SQL capability, analytical thinking, and ability to work with realistic ecommerce-style data.
Assessment focus
- SQL Query correctness and completeness
- Data handling and joins
- Clarity of logic and assumptions
- Explaining trade offs
- Ability to translate data into meaningful outputs
Outcome
Candidates who meet the required technical standard progress to interview. As a guideline, an overall score of around 80% typically indicates a strong submission.
Automated scoring tools can occasionally flag anomalies or underestimate strong approaches. For this reason, scores are not used in isolation. Submissions that demonstrate clear reasoning, sound methodology, and good problem-solving — even with a lower headline score (e.g. ~65%) — may still progress.
All submissions receive some level of review by the hiring manager to ensure thoughtful approaches are fairly assessed.
Note: All assessment data is synthetic. No real customer or company data is used in the discussion or fortmat of this repo
Purpose
Assess role motivation, prior experience, and ability to work effectively with stakeholders in an ecommerce and marketing analytics environment.
Structure
- 5 minutes — Introductions and context for the role
- 20 minutes — Structured discussion
- 5 minutes — Candidate questions
Discussion areas
- Motivation for the role and organisation
- Relevant experience and transferable skills
- Stakeholder alignment and communication
- Examples of cross-functional collaboration
- Approaches to solving complex problems
- Understanding and analysis of the ecommerce customer journey
Assessment criteria
- Communication (25 points)
- Alignment to the role (25 points)
- Stakeholder management experience (25 points)
- Overall role fit (25 points)
As a base, 75% pass through rate to submit to the next stage
Purpose
Assess deeper technical capability, analytical thinking, and how candidates approach real-world ecommerce analytics challenges.
Structure
- 50 minutes — Scenario-based, competency-led discussion
- 10 minutes — Candidate questions
Focus areas
- Ecommerce and marketing analytics concepts
- Data interpretation and problem-solving
- Trade-offs, assumptions, and decision-making
- Communicating insights to non-technical stakeholders
Assessment criteria
- Communication (25 points)
- Technical skills and data handling (25 points)
- Analytical thinking and problem-solving (25 points)
- Overall role fit (25 points)
As a base, 75% pass through rate to submit to the next stage
Purpose
Assess alignment with company values and how the candidate operates as an individual contributor. Standards set of questions the hiring manager can choose from, based on the business needs and requirements)
Structure
- 10 minutes — Introductions and reflection on the process
- 15 minutes — Competency-based questions mapped to company values
- 5 minutes — Candidate questions
Assessment criteria
- Aligned autonomy (20 points)
- Learning mindset (20 points)
- Trust and integrity (20 points)
- Collaboration and collective impact (20 points)
- Craft and quality (20 points)
As a base, 75% pass through rate to submit to the next stage
This process is designed to be transparent, structured, and respectful of candidate time.
It focuses not only on technical capability, but also on communication, judgement, and the ability to drive impact in a complex ecommerce environment. As with any interview process, discussions may vary slightly depending on role focus and candidate background.