Data Engineer

Citywire; Greater London; On-site; GBP 60,000 - 90,000; Full time

Benefits offered by this job

25 days annual leave

Employee Assistance Programme

Pension Scheme

Tech scheme

Personal development time

Job summary

Citywire's data platform powers products across the company, from industry ratings to production AI systems. We’re hiring a Data Engineer to help build pipelines and data models at the heart of it - taking requirements from stakeholder teams and turning them into tested, scheduled, monitored production systems.

This is a growth role, working directly with the platform lead on architecture, production engineering discipline, and collaborating with AI coding agents at scale.

Qualifications

• Experience building production data pipelines with robust data contracts and tests.
• Strong knowledge of dbt, Python, and SQL in real projects.
• Hands-on AWS deployment and debugging experience.
• Familiarity with containerized workflows and CLI-driven development.
• Ability to translate analyst requirements into production-ready pipelines.

Responsibilities

• Production data modelling: translate requirements into robust dbt models with tests and scheduling.
• Decompose legacy engines into modern AWS event-driven pipelines using Spark on EMR.
• Design data models powering AI platforms across funds, share classes, CRM, and finance systems.
• Ensure observability with logging, metrics, DLQ tracking, and alerting.
• Collaborate with analysts and data quality teams from requirements to deployment.

Skills

dbt

Python

SQL

AWS

Spark

Prefect

CI/CD testing

Data modeling

Data quality

Tools

Spark on EMR

Prefect

Job description

Citywire's data platform powers products across the company, both internal and external, from our industry ratings to our growing estate of production AI systems. We're hiring a Data Engineer to help build the pipelines and data models at the heart of it - taking requirements from stakeholder teams and turning them into tested, scheduled, monitored production systems. This is a growth role by design. You'll work directly with, and be mentored by, the platform lead - on architecture, on production engineering discipline, and on working effectively with AI coding agents at production scale.

What you’ll be doing:

• Production data modelling: Translate analyst requirements and SQL into robust, production-grade dbt models (source 12 warehouse 12 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.

What we’re looking for:

• 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.

Nice to Have (Genuinely learnable here - we will train you):

• 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.

Company Benefits

• 25 days annual leave (goes up to 28 after 3 years service, 29 after 4 and 30 after 5 years service)
• Employee Assistance Programme
• Pension Scheme
• Tech scheme plus so much potential to learn and develop within your role
• Opportunity to work with modern technologies and the opportunity to explore and innovate with new tech
• We also give you 10% of your working time for your own personal development.