Harnham

Analytics Engineering Insight Lead

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Analytics Engineering Insight Lead (Part-Time) based in London, with a 3-month contract at £300-£400 per day. Key skills include data ingestion, customer segmentation, and data quality management, requiring full-stack data expertise.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
400
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🗓️ - Date
December 20, 2025
🕒 - Duration
3 to 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
London, England, United Kingdom
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🧠 - Skills detailed
#"ETL (Extract #Transform #Load)" #Data Ingestion #Datasets #Data Quality #Customer Segmentation
Role description
Analytics Engineering Insight Lead (Part-Time) Location: Ideally 1 day per week in London Contract Length: 3 months Day Rate: £300-£400pd Start Date: January Overview This role sits at the intersection of analytics engineering and insight, supporting both growth and operational teams. The focus is on customer segmentation, lifecycle analysis, and generating high-quality, actionable insights. The successful candidate will be a full-stack data practitioner, comfortable owning data end to end rather than operating purely in reporting. Key Responsibilities Growth & Operations • Split time between growth-focused and operational analytics • Lead customer segmentation initiatives to deepen understanding of customer behaviour • Analyse and track customer movement through the end-to-end lifecycle • Ensure high standards of data quality, cleanliness, and reliability Reporting & Insights • Take ownership of the data ecosystem end to end, including: • Data ingestion • Data modelling • Data transformation • Understand and document: • Data origins • How data flows into and through the database • Model and join data across multiple datasets • Create new datasets where gaps exist • Prepare data so it is analysis- and report-ready • Work closely with stakeholders to contextualise insights and support decision-making Reporting vs Analysis Split • Much of the foundational data work is already in place • Expected time allocation: • 70% analysis and insight • 30% maintaining and improving data foundations