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- Tasks: Build and scale data pipelines using Python and SQL, integrating AI for faster delivery.
- Company: Fast-scaling fintech with a high-performing Data & AI team.
- Benefits: Competitive salary, flexible working, and opportunities for rapid learning and growth.
- Other info: Collaborative environment with excellent career development opportunities.
- Why this job: Join a dynamic team and make a real impact on innovative data products.
- Qualifications: Strong Python and SQL skills, experience in data engineering, and familiarity with AI workflows.
The predicted salary is between 60000 - 80000 £ per year.
We’re hiring an experienced Data Engineer to join a high-performing Data & AI team within a fast-scaling fintech. This is a hands-on role building modern data products end-to-end, using AI to accelerate delivery while maintaining strong engineering standards around governance, quality and scalability.
Over the last 12 months the team has attracted exceptional engineering talent, creating an environment where you’ll learn quickly and ship meaningful work. AI is actively integrated across the organisation, and you’ll help take those use cases further building reliable foundations and turning them into production ready capabilities.
You’ll contribute to high-impact workstreams including investor-style onboarding flows, entity and account structures, and a portfolio performance monitoring product that delivers monthly updates on how assets and exposures are progressing, and then rotate across domains over time to broaden your technical depth and product understanding.
What you’ll do:
- Build and scale data pipelines and data products using Python and SQL
- Use AI-enabled approaches to deliver high-quality data solutions faster, without compromising best practice
- Own delivery within your domain: data quality, documentation, accountability and maintainability
- Translate business needs into clear technical requirements and robust data models
- Build API-based integrations with source systems and deliver analytics-ready datasets
- Help improve how the team ships: testing, CI/CD patterns, orchestration and continuous improvement
What we’re looking for:
- Strong Python and SQL (comfortable coding from scratch)
- Influence on business operations (stakeholders) and API based integrations
- Experience building reliable ETL/ELT pipelines and production data models
- Strong data modelling fundamentals and ability to communicate with stakeholders
- Exposure to AI-enabled workflows is a plus (e.g., using AI tools to accelerate engineering, or supporting AI use cases with trusted data)
- DBT experience is a big plus
- Snowflake experience is helpful (not essential)
- 2+ years’ experience in data engineering or related fields (level flexible based on impact)
AI-Enabled Data Engineer for Scalable Pipelines employer: Siena Partnership
Contact Detail:
Siena Partnership Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI-Enabled Data Engineer for Scalable Pipelines
✨Tip Number 1
Network like a pro! Reach out to folks in the fintech space, especially those working with data and AI. Attend meetups or webinars, and don’t be shy about sliding into DMs on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and projects. Use GitHub or a personal website to highlight your Python and SQL prowess. This gives potential employers a taste of what you can do before they even meet you.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss how you've used AI in your past projects and how you can contribute to building scalable data solutions. Practice common interview questions with a friend or mentor.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our job listings and make sure your application stands out by tailoring it to the specific role and highlighting your relevant experience.
We think you need these skills to ace AI-Enabled Data Engineer for Scalable Pipelines
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your Python and SQL expertise, and any experience with AI-enabled workflows. We want to see how you can contribute to our high-performing Data & AI team!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data engineering and how you can help us build scalable pipelines. Share specific examples of your past work that align with our goals, especially around data quality and maintainability.
Showcase Your Projects: If you've worked on relevant projects, whether in a professional or personal capacity, make sure to mention them! We love seeing real-world applications of your skills, especially if they involve building reliable ETL/ELT pipelines or API integrations.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company culture and values!
How to prepare for a job interview at Siena Partnership
✨Know Your Tech Inside Out
Make sure you’re comfortable coding in Python and SQL from scratch. Brush up on your ETL/ELT pipeline knowledge and be ready to discuss how you've built reliable data models in the past. The more specific examples you can provide, the better!
✨Showcase Your AI Knowledge
Since this role involves AI-enabled workflows, be prepared to talk about any experience you have with AI tools. Share how you've used AI to enhance engineering processes or support data-driven decisions. This will show that you understand the integration of AI in data engineering.
✨Communicate Like a Pro
You’ll need to translate business needs into technical requirements, so practice explaining complex concepts in simple terms. Think about how you’ve communicated with stakeholders in the past and be ready to share those experiences during the interview.
✨Demonstrate Continuous Improvement Mindset
The team values improvement in shipping processes, so come prepared with ideas on testing, CI/CD patterns, or orchestration. Discuss any initiatives you’ve led or participated in that improved efficiency or quality in your previous roles.