Senior Analytics Engineer, AutogenAI
United Kingdom
£85-95k
Plus Stock Options
2 days a week in office
AI bid proposal writing tools
Open for applications
AI bid proposal writing tools
101-200 employees
Open for applications
£85-95k
Plus Stock Options
2 days a week in office
101-200 employees
Company mission
To create a new kind of product where users collaborate with Artificial Intelligence to produce relevant, impactful bid proposals.
Role
Who you are
- Strong Hands-On Analytics Capability: You are comfortable owning analytics delivery end-to-end, from raw data through to dashboards and executive-level insights
- Product-Minded Thinking: You focus on metrics that reflect real user and business value, and can help teams define what success looks like before work begins
- Analytics Engineering Fluency: You can write and review SQL, dbt models, and Python, and understand data pipelines well enough to ensure correctness and scalability
- Clear Communication & Judgment: You can challenge assumptions, explain trade-offs, and make complex data understandable to non-technical stakeholders
- Operational Data Leadership: You will have experience of balancing delivery across multiple stakeholders, with strong hands-on involvement to ensure quality, focus, and momentum. You may have some experience managing people or leading a small team
- Experience: Several years spent in analytics, data analytics, or analytics engineering roles, including hands-on delivery and stakeholder-facing work
- Industry Knowledge: Experience working in SaaS or product-led technology environments
- Technical Skills:
- Advanced SQL and dbt
- Data modelling (preferably familiar with Kimball approach)
- Redshift or similar cloud data warehouses
- Power BI dashboard design and modelling
- Python for analytics and code review
- AWS familiarity (Glue, ECS, Docker, Lambda)
- Alerting & Monitoring
- Education: Degree in a quantitative, technical, or related discipline, or equivalent practical experience
- Product Analytics: Experience defining tracking schemas, product KPIs, and analytics frameworks in collaboration with Product and Engineering
- Business Analytics: Experience translating business questions into clear metrics, analysis, and insights — with the judgment to focus on what drives real decision-making, not just what is technically measurable
What the job involves
- As Senior Analytics Engineer at AutogenAI, you will own analytics delivery across the business, ensuring data is trusted, used, and directly informs decision-making
- You’ll work end-to-end across metrics, models, and dashboards, translating complex data into clear and decision ready insights for product, commercial, and leadership teams
- AutogenAI has a modern data stack already in place, including a cloud data warehouse, analytics engineering layer, and semantic models supporting core business and product use cases
- In this role you’ll maximise the value of those foundations - sharpening metrics, improving adoption, extending models where needed, and making analytics a dependable input into day-to-day and executive decisions
- This is a hands-on role where you’ll spend a significant proportion of your time writing SQL and dbt models and building Power BI dashboards the business relies on weekly
- You’ll work closely with Product, Engineering, Commercial, and Finance, and play a key role in shaping how analytics evolves as the company scales. You’ll have one direct report from day 1, and this is a great opportunity for those looking to grow into leadership in time
- Hands-On Analytics Delivery: Design, build, and maintain core analytics outputs, including Power BI dashboards, ad-hoc analysis, and recurring reporting used by product, commercial, and leadership teams
- KPI & Metrics Ownership: Define, document, and own company and product KPIs, ensuring consistency, clarity, and trust in how performance is measured
- Product Analytics & Tracking: Partner with Product to define data goals for initiatives, and validate that data captured supports meaningful analysis
- Analytics Engineering & Data Modelling: Build and oversee analytics models using dbt and Redshift, preferably following the Kimball approach, ensuring data is well-structured, performant, and fit for downstream analysis and BI
- Stakeholder Engagement & Insight Translation: Work directly with senior leadership and shareholders to answer business questions, present insights, and recommend actions grounded in data
- Team Leadership & Quality Control: Line-manage a data engineer, review Python and SQL work, set standards for analytics engineering, and establish sustainable team processes
- Data Literacy & Visual Storytelling: Improve data literacy across the organisation and ensure insights are communicated clearly through well-designed dashboards and narratives
Salary benchmarks
Our take
Companies spend a large amount of time and resources writing copy, with sales writing alone being a significant spend. Not only is the cost of writing talents' time an issue, but it's also a constant worry to ensure that everyone is putting their best foot forward at all times and adhering to the company's style guide. The cost of miscommunications and errors in both internal and external communications is being minimised.
Utilising the latest advances in natural language processing, AutogenAI seeks to replace manually-generated content with text generated by its General Language Engine, also known as Genny-1. Its multi-disciplinary team works with clients to understand their needs, collates existing text to fine tune its model to that company's voice, then deploys Genny-1 in the areas of the business where it will have the greatest impact.
While this is likely to produce the best returns in bid proposals and other high value-add activities, AutogenAI can be applied to a wide range of internal and external business processes such as marketing, sales and public relations. As the use of AI becomes more mainstream, AutogenAI seeks to position itself as a vital tool in all forms of business communication, and substantial funding rounds show that it is well poised to achieve this.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Company benefits
- Hybrid-working with 3/4 office days in our beautiful King's Cross, London office
- Regular Team Socials
- Unlimited Annual Leave (Yes, you read right!)
- Laptop
Company HQ
City of London, London, UK
Leadership
Sean Williams
(Founder & CEO)Also a Board Memeber of the Sussex Community Development Association. Was previously Founder & CEO of Corndel and a Non Executive Director at ThnkWinDo and MyWorkSearch. Before that founded Guitar Club.
Share this job
View 4 more jobs at AutogenAI