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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Citywire - **Location:** Greater London, UK - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Amazon S3, Business Logic, BigQuery, Continuous Integration, Data Stores, Software Debugging, Distributed Systems, Python (Programming Language), Operational Databases, Standard Sql, Shell Script, SQL Databases, Data Logging, Apache Spark, Event Driven Architecture, Amazon Relational Database Service, Containerization, AI Platforms, Functional Programming, Amazon Simple Queue Service (SQS) - **Published:** August 30, 2026 - **Apply:** https://www.collegerecruiter.com/job/2815455764-data-engineer ## About the Role * Real dbt experience: You've built and maintained models in a genuine project - incremental logic, tests, an understanding of why downstream consumers matter. It doesn't need to have been enormous; it needs to have been real. BigQuery experience is a plus; another warehouse is fine. * Solid Python and SQL skills, with the instinct that code going to production deserves tests. * Practical AWS Experience: You have hands-on experience deploying and debugging in AWS. You don't need to know every service we use on day one - we'll teach you our specific stack. * Strong CLI Skills: Proficient with terminal-driven workflows, containerized environments, and shell scripting for debugging, automation, and local development. * Pragmatic AI Tooling: You leverage AI coding assistants to speed up your workflow, but bring critical oversight to their output - reviewing, testing, and verifying generated code rather than shipping it on faith. * Data Intuition & Rigor: You look beyond passing CI/CD checks. When a pipeline runs green but the outputs look off, you dig into the numbers, comparing runs, spotting unexpected anomalies, and validating the business logic behind the data. * Accountability & Resilience: You take pride in what you build. You learn from production mistakes, own the outcome, and prefer holding accountability for your own pipelines over handing off maintenance to someone else. * Collaborative Communication: You can sit side-by-side with analysts, understand the intent behind their SQL, and partner with them to translate complex business logic into efficient, production-ready solutions., * Frameworks & Tools: Spark on EMR, Prefect (or experience transferring from Airflow/Dagster), OpenSearch. * Architecture: Event-driven design patterns, SurrealDB or graph data stores. * Domain Knowledge: Financial services or asset management context. ## Description * Production data modelling: Translate analyst requirements and SQL into robust, production-grade dbt models (source * warehouse * reporting layers). You'll own data contracts, documentation, testing, and scheduling, with orchestration managed via Prefect. * Large-scale fund and manager performance computation: Help decompose a legacy performance engine into a modern, event-driven AWS architecture (EventBridge, SQS, Lambda, S3, RDS). You'll build parallel compute pipelines using Spark on EMR (no deep prior Spark experience needed, just a strong curiosity for distributed systems). * Data models for AI systems: Partner with the Platform Lead to design, build, and maintain the data models powering our AI platform - spanning fund and share class data, clickstream interactions, and CRM and finance systems. * Alerting and observability: Ensure operational health across all pipelines via structured logging, metrics, DLQ tracking, and purposeful alerting. We view observability as a core engineering practice and will support your growth in designing resilient event-driven systems. * Work directly with the analyst team and the data quality team, from requirement through deployment. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [WeAreDevelopers LIVE - CSS is DOOMed](https://www.wearedevelopers.com/videos/1838-wearedevelopers-live-css-is-doomed) - [Making Data Warehouses fast. 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