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- Tasks: As an Analytics Engineer, you'll optimise data pipelines and collaborate with teams to enhance data insights.
- Company: Join Fyxer AI, a fast-growing startup revolutionising productivity with innovative AI tools.
- Benefits: Enjoy a competitive salary, equity options, and a vibrant office culture in London.
- Why this job: Be part of a passionate team driving meaningful change in the AI space with real ownership.
- Qualifications: 2+ years in data roles, expert SQL skills, and experience with modern ELT stacks required.
- Other info: Work in a dynamic environment with opportunities for rapid growth and learning.
The predicted salary is between 60000 - 84000 £ per year.
Your title will be Analytics Engineer. This role pays £70k-£90k + equity.
We work Mon-Thu in our office in Chancery Lane, London.
What are we building?
Great people are working on overdrive to do a great job, but are held back because their inbox is failing them. We’re building an AI Productivity tool that eliminates the admin burden for people who work client-facing roles. Fyxer AI simplifies these tasks by organizing your inbox, drafting replies in your own voice, and taking crisp meeting notes. It works directly inside Outlook, Gmail, & Zoom.
How has it been going?
Since our launch in May 2024, we’ve grown from $0 to $8 million in revenue, serving thousands of paying users. In February 2025, we raised a $10 million Series A to accelerate our path to $50 million in revenue—backed by top-tier investors. We spent Q4 2024 in San Francisco at HF0, learning from experts. We’re now at the stage of hypergrowth and are looking for the best of the best.
What do we value?
We believe small, passionate teams outperform big, unfocused ones every time. We’re looking for people who bring intensity, creativity, and genuine care to their work. You’ll take on meaningful responsibilities from day one, with opportunities to grow faster than at most companies.
Requirements
What will I do?
- Maintain and improve pipelines between our data warehouse (Bigquery) and various data sources.
- Build improvements to our data transformation process using SQL and dbt.
- Make architecture decisions regarding data infrastructure.
- Work with stakeholders to agree metrics that need to be monitored on an ongoing basis.
- Ensure data is modelled in the correct format to support data visualisation and more detailed analyses.
What does our ideal hire look like?
- At least 2 years as a Data Engineer or hands-on Data Analyst.
- You’ve worked at an early-stage tech company.
- You have an expert level understanding of SQL and a modern ELT stack.
- Experience with DBT is essential.
- You can interface with both technical and non-technical stakeholders.
- Urgency and intensity in your work.
Our tech stack
- BigQuery as our data warehouse.
- Metabase for data visualisation.
- Fivetran to pipe raw data from third-party tools into our data warehouse.
- dbt hosted on Github Actions for transformation of raw data.
- Census for reverse ETL.
The application process
- Submit your CV (no need for a cover letter).
- An initial call with someone from the Fyxer AI team.
- Live coding - SQL.
- Architecture interview.
- Meet Richard - CEO.
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Information Technology
Industries: IT Services and IT Consulting
Analytics Engineer (AI Startup) employer: Fyxer AI
Contact Detail:
Fyxer AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer (AI Startup)
✨Tip Number 1
Familiarise yourself with Fyxer AI's product and its unique features. Understanding how their AI productivity tool simplifies tasks for client-facing roles will help you articulate your enthusiasm and fit for the role during interviews.
✨Tip Number 2
Brush up on your SQL skills and be prepared for the live coding session. Practising common SQL queries and data transformation techniques will give you the confidence to showcase your technical abilities effectively.
✨Tip Number 3
Research the company’s growth trajectory and recent funding rounds. Being knowledgeable about their achievements and future goals will demonstrate your genuine interest in being part of their journey.
✨Tip Number 4
Prepare to discuss your experience with data pipelines and stakeholder collaboration. Highlight specific examples where you've successfully interfaced with both technical and non-technical teams to solve data-related challenges.
We think you need these skills to ace Analytics Engineer (AI Startup)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience as a Data Engineer or Data Analyst. Focus on your ownership of data pipelines and any specific projects that demonstrate your skills in SQL and dbt.
Showcase Technical Skills: Emphasise your expert-level understanding of SQL and familiarity with the ELT stack. Mention any experience with tools like BigQuery, Metabase, and Fivetran to align with the company's tech stack.
Highlight Stakeholder Interaction: Include examples of how you've interfaced with both technical and non-technical stakeholders. This will show your ability to recommend intuitive data structures and communicate effectively across teams.
Express Your Passion: In your application, convey your enthusiasm for working in a fast-paced startup environment. Highlight your urgency and intensity in your work, as these qualities are highly valued by Fyxer AI.
How to prepare for a job interview at Fyxer AI
✨Showcase Your SQL Skills
Since the role requires an expert level understanding of SQL, be prepared to demonstrate your skills during the live coding session. Brush up on complex queries and data manipulation techniques to impress your interviewers.
✨Understand the Tech Stack
Familiarise yourself with the tools mentioned in the job description, such as BigQuery, dbt, and Fivetran. Being able to discuss how you've used similar tools or how you would approach using these can set you apart from other candidates.
✨Prepare for Architecture Decisions
During the architecture interview, be ready to discuss your thought process behind data infrastructure decisions. Think about scalability, performance, and ease of use, and be prepared to justify your choices with examples from your past experience.
✨Communicate Effectively with Stakeholders
The role involves interfacing with both technical and non-technical stakeholders. Practice explaining complex data concepts in simple terms, and prepare examples of how you've successfully collaborated with different teams in previous roles.
