At a Glance
- Tasks: Create AI-driven analytics for trading teams using Databricks and modern LLM workflows.
- Company: Dynamic fintech company in London with a hybrid working model.
- Benefits: Competitive daily rate, flexible working hours, and opportunities for skill development.
- Other info: Collaborative environment with potential for career advancement.
- Why this job: Join a cutting-edge team and shape the future of trading analytics.
- Qualifications: Experience with Databricks, Spark, and strong data engineering skills required.
The predicted salary is between 60000 - 80000 £ per year.
Duration: Contract
Workload: Full time hours
Setup: Freelance (Daily rate / Limited Company / Umbrella / Sole Trader)
Location: London - hybrid working
We need an AI Engineer with a strong data engineering core to build AI‑powered analytics for front‑office trading teams using Databricks, Spark, and modern LLM workflows.
Key Responsibilities:
- Design and deliver AI‑driven analytics for traders, including seasonality, correlations, regression, forecasting, and scenario modelling.
- Build scalable, reusable data pipelines in Databricks using PySpark, Spark SQL, Delta Lake, and Unity Catalog.
- Perform statistical and econometric analysis on large market and fundamentals time‑series datasets.
- Work directly with traders and analysts to turn ambiguous questions into production‑ready tools and clear insights.
- Implement LLM and agentic workflows (prompt engineering, LangGraph, MCP, tool calling, retrieval, guardrails).
- Productionise solutions with testing, observability, versioning, documentation, and CI/CD.
Must‑Have Skills:
- Hands‑on Databricks and Spark expertise (PySpark, SQL, Delta, Unity Catalog).
- Strong data engineering background: ingestion, modelling, orchestration, performance tuning.
- Solid statistics/econometrics for market time series.
- Experience building and integrating LLM solutions.
- Excellent communication and stakeholder engagement skills.
Nice‑to‑Have:
- Commodity or financial trading background.
- Knowledge of market microstructure, supply/demand fundamentals, or risk.
Training & Content Engineer employer: Airswift
As a leading employer in the financial technology sector, we offer an innovative and collaborative work environment in London, where hybrid working allows for flexibility and work-life balance. Our commitment to employee growth is evident through continuous learning opportunities and hands-on projects that empower you to develop cutting-edge AI solutions for trading analytics. Join us to be part of a dynamic team that values creativity, diversity, and impactful contributions to the trading landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Training & Content Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with traders and analysts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Databricks, Spark, and LLMs. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss how you've tackled ambiguous problems and turned them into clear insights, just like you'd do in the role.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications come directly from candidates who are excited about joining us. Plus, it makes it easier for us to keep track of your application.
We think you need these skills to ace Training & Content Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Training & Content Engineer. Highlight your experience with Databricks, Spark, and LLMs, and don’t forget to showcase any relevant projects that demonstrate your skills in building AI-driven analytics.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about the role and how your background aligns with our needs. Be specific about your experience with data pipelines and statistical analysis, and show us your enthusiasm for working with traders.
Showcase Your Communication Skills:Since this role involves working closely with traders and analysts, it’s crucial to highlight your communication skills. In your application, mention instances where you’ve successfully turned complex data into clear insights or tools that others can use.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss out on any important updates from us. Plus, it shows you’re keen on joining the StudySmarter team!
How to prepare for a job interview at Airswift
✨Know Your Tech Inside Out
Make sure you’re well-versed in Databricks, Spark, and LLM workflows. Brush up on PySpark and SQL, and be ready to discuss how you've used these tools in past projects. The more specific examples you can provide, the better!
✨Showcase Your Analytical Skills
Prepare to talk about your experience with statistical and econometric analysis. Think of a few scenarios where you’ve turned complex data into actionable insights for traders. This will demonstrate your ability to handle the key responsibilities of the role.
✨Communicate Clearly
Since excellent communication is a must-have skill, practice explaining technical concepts in simple terms. You might be asked to describe how you would turn ambiguous questions into clear insights, so think through a couple of examples beforehand.
✨Engage with Stakeholders
Be ready to discuss how you’ve worked with traders and analysts in the past. Highlight your stakeholder engagement skills and how you’ve collaborated to deliver production-ready tools. This shows you can bridge the gap between tech and trading teams.
