Senior Data Engineer

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Wrisk

WebsiteLinkedInAlle Stellen

11 - 50 Mitarbeiter

🚘 Automobilindustrie

🛡️ Versicherung

💳 Fintech

Automotive • Insurance • Fintech

Wrisk ist ein Unternehmen, das eine anpassbare Plattform für die Automobilindustrie bereitstellt, um nahtlose digitale Versicherungserlebnisse zu liefern. Die Plattform ist darauf ausgelegt, differenzierte Versicherungslösungen schnell zu erstellen, einzuführen und in großem Umfang zu verwalten. Durch die Nutzung von Echtzeitdaten und der Kraft der Telematik bietet Wrisk innovative Versicherungsoptionen, die auf die Bedürfnisse von Kunden und Unternehmen zugeschnitten sind. Wrisk fungiert als voll autorisierte Versicherungsvermittler im Vereinigten Königreich und hat die Expertise, um Vermittlungs- und Beratungsdienste in anderen Märkten durch etablierte Partnerschaften anzubieten. Die Plattform wird von Automobilherstellern, Vertriebsgesellschaften, Finanzhäusern, MGAs und Versicherern genutzt, um kundenorientierte und transparente Versicherungslösungen anzubieten. Wrisk steht an der Spitze der InsurTech-Bewegung und kombiniert Technologie und Markterfahrung, um Chancen und Herausforderungen in der Versicherungsbranche anzugehen.

Beschreibung

• Design, build, and operate data ingestion and ETL/ELT pipelines for our data systems that power Atto products and customer-facing applications. • Build and maintain our data platform architecture and infrastructure, including data pipelines, warehouses that power analytics and product features and reporting. • Implement data modelling, schema design, and data contracts to make datasets easy to consume. • Introduce and maintain observability, data quality checks, and automated testing for our production data flows. • Driving impact at scale by improving data workflows, service reliability, and making Atto’s capabilities faster, more reliable and widely accessible. • Collaborate with product managers and cross-functional teams to translate market signals and customers’ needs into innovative data-driven solutions. • Create new systems and approaches, while continuously improving and scaling existing ones for performance, reliability, and efficiency. • Conduct deep analysis of transactional datasets to validate data models, surface data quality issues, and propose engineering fixes. • Optimise performance and cost of data processing and storage across cloud services. • Communicate technical findings and recommendations clearly to both technical and non-technical stakeholders across the business. • Stay current with industry developments, emerging technologies, and best practices in data engineering.

🎯 Anforderungen

• A Bachelor's degree in Computer Science, Data/Software Engineering, or a related discipline. • 5+ years of hands-on experience in data engineering with a proven track record of delivering scalable, production-grade data platforms and data models. • Strong SQL skills and proven experience designing, building and optimising data pipelines and data warehouse schemas. • Strong proficiency in Python for production data engineering with a focus on building maintainable, testable and clean code. • Track record of implementing data quality, observability, monitoring and testing practices. • Solid experience with at least one cloud provider (Azure, AWS or GCP), and their managed data services. • Experience with CI/CD, infrastructure-as-code and working in containerised environments. • Familiarity with modern data stack tools: Databricks, Snowflake or RedShift, etc. • Experience working with reporting and modelling tools such as Power BI, including designing performant data models and supporting self-serve analytics. • Advanced experience in pattern recognition with the ability to translate complex data into actionable insights. • A results-oriented mindset, able to take concepts from ideation through to tangible outputs. • Comfortable working in a fast-paced, delivery-focused environment, balancing multiple priorities with agility. • A proactive and collaborative approach, with a willingness to iterate, share knowledge, and challenge assumptions constructively • Bonus Points (We’re getting greedy) • Experience building or scaling data platforms in large-scale, regulated data environments. • Experience with DevOps for data, platform engineering, or building large data pipelines and real-time data streaming systems. • Exposure to working in a high-growth, evolving environment where the customer is at the heart of product and engineering decisions.

🏖️ Vorteile

• A team of passionate, interesting people committed to your development and success • £70-£80k gross/pension • Personal training and Continuous Professional Development budget (CPD) • Uncapped bike to work scheme • Half-day Fridays every last week of the month to recharge • Wellness partnerships • In-person and virtual team events and workshops • Volunteering (Social Good Connect partnership) • 33 days holiday allowance to take when you want • £200 home working contribution to make sure you have everything you need to do your best work (get comfy - we want you to stay) • Ask us about our remote-first, flexible culture - this is core to who we are, and we're rated one of Scotland's most flexible employers