At a Glance
- Tasks: Own and enhance NALA's data transformation layer for impactful analytics.
- Company: Join a forward-thinking company at the forefront of data innovation.
- Benefits: Enjoy 27 days off, competitive salary, and opportunities for professional growth.
- Other info: Dynamic role with mentorship opportunities and a clear roadmap for career advancement.
- Why this job: Shape the future of analytics with cutting-edge technology and AI capabilities.
- Qualifications: 4+ years in dbt, strong SQL and Python skills, and data modelling expertise.
The predicted salary is between 60000 - 80000 £ per year.
Your Mission: As Senior Analytics Engineer, you'll own, uplift and maintain NALA's data transformation layer — the foundation that all reporting, governed metrics, self‑serve analytics and AI‑powered capabilities depend on. Your work will add semantic richness, structure and governance to NALA's data, ensuring every model is documented, tested and described in a way that both humans and AI agents can interpret and trust. Agentic analytics is arriving fast, and this role exists to help ensure NALA's data foundation is ready for it.
Your Responsibilities in this Role:
- Own the transformation layer (dbt + Snowflake) — refactoring, enforcing best practices, and evolving our data stack to a best‑in‑class standard.
- Take ownership of streaming data pipelines alongside batch transformation — ensuring real‑time and near‑real‑time data flows are reliable, cost‑efficient and well‑integrated into the broader data architecture.
- Establish and enforce coding & agentic coding standards, systematic testing and documentation as CI‑enforced defaults across all data models.
- Optimise warehouse performance and cost efficiency, identifying and resolving the query patterns and materialisation choices driving unnecessary spend.
- Build the foundation for AI‑powered self‑serve by ensuring models carry the semantic richness and documentation that agents need to return reliable answers.
- Scope and resolve orchestration decisions (dbt Cloud vs Dagster) and own the infrastructure roadmap for the transformation layer.
- Support and mentor analysts on analytics engineering best practices, raising the engineering standard across the team.
Must-have requirements:
- 4+ years hands‑on experience with dbt (ideally fusion) — building, refactoring and maintaining production‑grade transformation layers.
- Strong SQL, Python and data modelling skills with a clear understanding of warehousing and modern data architecture.
- Snowflake or Databricks experience including query performance tuning and cost optimisation.
- Deep proficiency with AI‑assisted development workflows (Cursor, Windsurf, Claude Code) to force‑multiply engineering output and accelerate delivery.
- Track record of implementing testing, CI/CD, documentation standards and PR review workflows in dbt projects.
- Comfortable owning an infrastructure roadmap — can assess the current state, propose a plan and execute without being directed step‑by‑step.
Nice to have requirements:
- Semantic layer experience (Cube, dbt Semantic Layer) and understanding of how governed metric definitions sit on top of a transformation layer.
- Familiarity with orchestration tools (Dagster, Airflow, dbt Cloud etc).
- Experience with Hex or similar modern BI/notebook platforms.
- Experience in fintech, payments or regulated environments where data accuracy and governance carry real business consequences.
- Familiarity with experimentation frameworks and product analytics.
Success in the role looks like:
- 3-Month Metrics: Full ownership of the transformation layer and warehouse, with a clear understanding of the current architecture, cost drivers and priorities.
- 6-Month Metrics: Full ownership of warehouse coding standards, data architecture and infrastructure. Measurable improvement in the cost and efficiency of supplying data to the business. A clear data infrastructure roadmap delivered for the following 6 months.
Benefits: 27 Days Off Plus UK
Senior Analytics Engineer in London employer: Nala
At NALA, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. As a Senior Analytics Engineer, you'll not only have the opportunity to shape our data transformation layer but also benefit from extensive professional growth opportunities, mentorship, and a generous leave policy of 27 days off plus UK holidays. Our commitment to employee well-being and development, combined with our cutting-edge technology and focus on AI-powered analytics, makes NALA a truly rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Analytics Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect on LinkedIn. 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 dbt, Snowflake, or any AI-powered analytics. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to data transformation and analytics engineering. Practice explaining your thought process clearly, as communication is key in this role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Analytics Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Senior Analytics Engineer. Highlight your experience with dbt, Snowflake, and any relevant projects that showcase your skills in data transformation and analytics engineering.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about data and how your background aligns with our mission at NALA. Share specific examples of how you've uplifted data layers or optimised performance in past roles.
Showcase Your Technical Skills:Don’t shy away from listing your technical proficiencies! We want to see your SQL, Python, and data modelling skills front and centre. If you’ve worked with AI-assisted development workflows, make sure to mention that too!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Nala
✨Know Your Tools Inside Out
Make sure you’re well-versed in dbt, Snowflake, and any other tools mentioned in the job description. Brush up on your SQL and Python skills, and be ready to discuss how you've used these technologies in past projects. Being able to share specific examples will show that you’re not just familiar with them, but that you can truly leverage them.
✨Demonstrate Your Problem-Solving Skills
Prepare to talk about challenges you've faced in data transformation or analytics engineering. Think of a couple of scenarios where you optimised performance or resolved issues with data pipelines. This will highlight your ability to think critically and act decisively, which is crucial for this role.
✨Showcase Your Documentation Practices
Since documentation is key in this role, be ready to discuss how you’ve implemented testing, CI/CD, and documentation standards in your previous work. Bring examples of how you’ve ensured that your models are well-documented and easy for others to understand, as this will demonstrate your commitment to best practices.
✨Understand the Bigger Picture
Familiarise yourself with NALA's mission and how the Senior Analytics Engineer role fits into it. Be prepared to discuss how you can contribute to building a robust data foundation that supports AI-powered capabilities. Showing that you understand the strategic importance of your role will set you apart from other candidates.
