Senior Analytics Engineer, United Kingdom

AutogenAI is a leader in Generative AI SaaS, transforming how organisations create and optimise winning bids, tenders and proposals through cutting-edge natural language processing technology. We are one of the fastest-growing AI companies in the world, expanding rapidly to meet the increasing demand for AI-driven solutions across sectors. 

Our innovation stems from a belief that language technology will revolutionise business communication over the next decade. We empower our clients to grow faster and more efficiently by delivering bespoke AI language engines tailored to their needs, saving time, improving content quality, and boosting win rates in highly competitive markets. 

We drive AutogenAI’s growth by fostering a culture where innovation and ambition thrive, building a company where everyone can have a career-defining experience. As we scale, we invite passionate professionals to join our journey of innovation, helping shape the future of AI-powered business solutions. 

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. 

• 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. 

• Competitive Salary: £85,000 - £95,000 depending on specific experience and qualifications relevant to the role.   
• Stock Options: Meaningful equity in the company. 
• Retirement Plan: Pension scheme to help secure your future.  
• Paid Time Off: Unlimited vacation (Yes, you read right!) 
• Flexible Work Options: Hybrid working arrangements
• Private Healthcare: Bupa Medical and Dental cover 
• Life Insurance: Peace of mind for you and your family
• Paid parental leave: 16 weeks if you’ve just given birth, 4 weeks if your partner has just given birth (after one year of year of service) 
• Additional Perks: Your choice of laptop (Mac or Windows), regular company events to connect with teammates, and opportunities for continued professional development. 

• Customers, Always: Everything starts with our customers. We walk in their shoes, speak their language, and build for their delight and success. We win when they win.
• Make It Happen: We move fast and take ownership. No waiting, no red tape – just action, urgency, and focus on outcomes. We ask for forgiveness, not permission.
• Learn and Invent: We stay curious. We learn what we can from past masters - and make up the rest. Change is constant, and so is our growth.
• Act Like Owners: Titles don’t solve problems - people do. We own challenges, break the rules when it’s necessary, and focus on what matters.
• Turn It Up to 11: There is no “Good enough”. We raise the bar, push boundaries, and keep building. There’s always a next level.
• Lead With Respect: We listen first, speak honestly, and value every perspective. Integrity, follow-through, and kindness matter.
• Build Trust Through Transparency: We default to openness. We give feedback, share information, and assume positive intent - no secrets, no silos.

AutogenAI is an equal opportunity employer dedicated to fostering a diverse and inclusive workplace. We do not discriminate on the basis of race, colour, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by federal, state, or local laws. 

We encourage applications from individuals of all backgrounds, including those with disabilities and veterans. Our hiring decisions are based on qualifications, merit, and business needs.  

At AutogenAI we value the unique perspectives each employee brings and strive to provide an equitable environment. If you require reasonable accommodations during the application or interview process, please let us know, and we will gladly assist you.