Senior Data Engineer

🕒 il y a 10 jours

🇬🇧 Royaume-Uni – Télétravail

💵 £90 000 - £110 000 / an

⏰ Temps Plein

🟠 Senior

🚰 Ingénieur Data

🇬🇧 Parrain de Visa de Travailleur Qualifié UK

Cette entreprise a parrainé des visas de Travailleur Qualifié du Royaume-Uni par le passé.

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Codat

Site WebLinkedInTous les Emplois

201 - 500 employés

Fondée en 2017

💼 Conseil

📦 Logistique

🔌 API

Consulting • Logistics • API

Codat est une plateforme B2B de connectivité et d'analytique de données financières qui propose des API pour agréger les données comptables, ERP et de paiements provenant de petites et moyennes entreprises. Les institutions financières, banques, prêteurs et fintechs utilisent Codat pour automatiser les workflows comptables, obtenir des insights sur les dépenses et rationaliser les décisions de crédit grâce à un partage de données fluide et des analyses pilotées par l'IA. Codat connecte des centaines de milliers d'entreprises et offre des produits de données sur mesure pour des cas d'usage tels que l'émission de cartes commerciales, l'automatisation comptable et les prêts aux entreprises.

Description

• Write production code every day, most likely in Python, building and maintaining the data pipelines that power our Insights products. • Own the full lifecycle of your projects, from understanding the data domain through to pragmatic design, shipping, and keeping things running reliably in production. • Set and lead the technical direction of the Insights platform, and communicate it openly across engineering and the wider business, so product and commercial colleagues understand the choices you are making and why. • Help raise engineering standards across the team and improve technical quality through strong engineering practice, including testing, observability, data quality checks, and clean, maintainable code. • Make AI your default way of working, and find opportunities to apply it across our products and pipelines where it delivers real value, from research and prototyping through to more operational uses such as agents that help diagnose and fix pipeline issues. • Help lay the foundations for our emerging MCP and semantic layer, so our data becomes something both people and AI systems can query and reason over.

🎯 Exigences

• Strong software engineering fundamentals: you write well-tested, production-ready Python and care about maintainability, observability, and operational excellence. • A track record of building data pipelines and production systems from the ground up, rather than mainly configuring managed services or wiring off-the-shelf tools together. You can describe complex logic you've written and the engineering problems you had to solve. • Solid experience with modern data engineering tools and patterns, with real depth in several of SQL, Spark, Databricks/Delta Lake, orchestration tools (Dagster, Airflow, Temporal), and dbt. • Comfort with modern deployment practices: CI/CD, containerisation (Docker), and cloud-based infrastructure. It's a bonus if you've shaped these for a team, not only worked within them. • A product mindset: you want to understand the business domain and use that understanding to shape what gets built, not only how. You're comfortable pushing back or proposing a different approach when your read of the data and the domain calls for it. • Strong communication skills: you can explain and build support for your ideas with peers, managers, and non-technical stakeholders, and you're comfortable holding a visible technical position and bringing people with you. • AI as a default part of how you work, with evidence of real efficiency gains and creative use beyond code generation, such as research, building domain knowledge, or prototyping. • Nice to have: exposure to the building blocks of AI-ready data, such as semantic layers, ontologies, or text-to-SQL, plus any experience applying AI operationally within data platforms or pipelines. This won't be your main focus, but it will help as our platform grows to support an MCP.

🏖️ Avantages

• Offers Equity