Founding Data Engineer

🕒 May 27

🏢🏡 London – Hybrid

💵 £95k - £130k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

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Plain Concepts

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2006

🤖 Artificial Intelligence

🔒 Cybersecurity

Artificial Intelligence • Cybersecurity • Cloud Computing

Plain Concepts is an innovative technology company committed to delivering customized solutions across a wide array of digital needs. With a focus on cutting-edge areas like Artificial Intelligence, cybersecurity, cloud computing, and Internet of Things (IoT), Plain Concepts is a partner for companies looking to enhance operations and secure their digital landscapes. As a recognized Microsoft AI Partner, Plain Concepts aims to transform data into insightful information and improve business applications through bespoke IoT developments. Additionally, the company fosters revolutionary advancements in augmented and virtual reality, while driving digital transformation initiatives with Microsoft 365 and a strong focus on sustainability and social commitment.

📋 Description

• Rebuild our data warehouse: own the architecture, schemas, and core datasets with clean pipelines and a unified event taxonomy established with Engineering. • Deliver trusted, reusable data products: foundational datasets that power analytics, reporting, in-app features, and AI, anchored on a joinable customer/account spine across product, billing, and CS context. • Stand up data observability: quality checks, freshness, lineage, schema drift, and incident response, so the business can trust what it sees. • Own in-app reporting: ship the analytics features that help support leaders turn their data into better decisions. • Enable self-serve: evolve our data layer, dashboards, and documentation so every team can run their own analysis without a ticket. • Lay the retrieval layer behind our AI agent's customer context. • Partner across the company: work with GTM, CX, Product, and Engineering to translate questions into scalable models and datasets.

🎯 Requirements

• Have built modern analytics stacks end-to-end (warehouse, transformations, semantic layer, governance) from zero, ideally more than once. • Are strong with SQL, BigQuery, and dbt/Dataform. • Have experience building user-facing analytics or AI retrieval layers using real-time data platforms (e.g., Tinybird, ClickHouse). • Care about data quality, trust, and reusability as much as shipping speed. • Take initiative and measure your work by end-user impact, not elegant abstractions. • Communicate clearly and build alignment without heavy process.

🏖️ Benefits

• Offers Equity