At a Glance
- Tasks: Own analytics delivery, translating complex data into clear insights for decision-making.
- Company: Join AutogenAI, a forward-thinking tech company focused on innovation and collaboration.
- Benefits: Enjoy a competitive salary, stock options, unlimited vacation, and remote work flexibility.
- Why this job: Make a real impact by driving data-driven decisions in a dynamic environment.
- Qualifications: Experience in analytics roles, strong SQL and Python skills, and a product-focused mindset.
- Other info: Be part of a diverse team that values transparency, respect, and continuous learning.
The predicted salary is between 68000 - 76000 ÂŁ per year.
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, decision‑ready insights for product, commercial, and leadership teams.
Key Responsibilities
- Design, build and maintain core analytics outputs, including Power BI dashboards, ad‑hoc analysis, and recurring reporting.
- Define, document and own company and product KPIs, ensuring consistency, clarity and trust in how performance is measured.
- Partner with Product to define data goals for initiatives, and validate that data captured supports meaningful analysis.
- Build and oversee analytics models using dbt and Redshift, preferably following the Kimball approach.
- Engage with senior leadership and stakeholders to answer business questions, present insights and recommend actions grounded in data.
- Line‑manage a data engineer, review Python and SQL work, set standards for analytics engineering, and establish sustainable team processes.
- Improve data literacy across the organisation and ensure insights are communicated clearly through well‑designed dashboards and narratives.
What You’ll Bring
- Strong hands‑on analytics capability – from raw data through to dashboards and executive‑level insights.
- Product‑mindful thinking – focus on metrics that reflect real user and business value.
- Analytics engineering fluency – write and review SQL, dbt and Python; understand data pipelines.
- Clear communication and judgment – challenge assumptions, explain trade‑offs and make data understandable to non‑technical stakeholders.
- Operational data leadership – balance delivery across stakeholders, manage people or lead a small team.
Requirements
- Several years in analytics, data analytics or analytics engineering roles, including hands‑on delivery and stakeholder‑facing work.
- Experience in SaaS or product‑led technology environments.
- Advanced SQL and dbt.
- Data modelling (preferably familiar with Kimball).
- Redshift or similar cloud data warehouse.
- Power BI dashboard design and modelling.
- Python for analytics and code review.
- AWS familiarity (Glue, ECS, Docker, Lambda).
- Alerting & monitoring.
- Degree in a quantitative, technical, or related discipline, or equivalent practical experience.
- Experience defining tracking schemas, product KPIs, and analytics frameworks with Product and Engineering.
- Experience translating business questions into clear metrics, analysis, and insights.
Compensation and Benefits
- Competitive salary: £85,000 – £95,000 depending on experience.
- Stock options.
- Pension scheme.
- Unlimited vacation.
- Remote working arrangements.
- Bupa medical and dental cover.
- Life insurance.
- Paid parental leave: 16 weeks for birth, 4 weeks for partner’s birth.
- Laptop choice (Mac or Windows), regular company events and professional development opportunities.
Values in Action
- Customers, always – we walk in their shoes, speak their language, and build for their delight.
- Make it happen – move fast, take ownership, no red tape.
- Learn and invent – stay curious, adapt, grow.
- Act like owners – titles don’t solve problems, people do.
- Turn it up to 11 – no “good enough”, continuously push boundaries.
- Lead with respect – listen first, speak honestly, value every perspective.
- Build trust through transparency – open communication, feedback, no silos.
Equal Employment Opportunity Statement
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. If you require reasonable accommodations during the application or interview process, please let us know, and we will gladly assist you.
Senior Analytics Engineer, United Kingdom employer: AutogenAI
Contact Detail:
AutogenAI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Analytics Engineer, United Kingdom
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Prepare for those interviews! Research the company and its culture, and think about how your skills align with their needs. We want you to shine when it’s your turn to talk!
✨Tip Number 3
Show off your work! Create a portfolio of your analytics projects, dashboards, or any relevant work. It’s a great way to demonstrate your hands-on experience and make a lasting impression.
✨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!
We think you need these skills to ace Senior Analytics Engineer, United Kingdom
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Senior Analytics Engineer. Highlight your hands-on analytics experience, especially with SQL, dbt, and Power BI. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about analytics and how you can contribute to our mission at AutogenAI. Keep it concise but impactful – we love a good story!
Showcase Your Projects: If you've worked on any relevant projects, don’t hold back! Include links or descriptions of dashboards you've built or analytics models you've developed. We’re keen to see your work in action and how it’s made a difference.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get the best experience possible. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at AutogenAI
✨Know Your Analytics Inside Out
Make sure you’re well-versed in the analytics tools and methodologies mentioned in the job description, like SQL, dbt, and Power BI. Prepare to discuss your hands-on experience with these technologies and how you've used them to deliver insights that drive decision-making.
✨Showcase Your Communication Skills
Since you'll be translating complex data for non-technical stakeholders, practice explaining your past projects in simple terms. Think about how you can convey technical concepts clearly and effectively, as this will be crucial in your role.
✨Prepare for Leadership Engagement
You’ll be engaging with senior leadership, so come prepared with examples of how you've previously presented insights and recommendations. Highlight your ability to challenge assumptions and provide data-driven solutions that align with business goals.
✨Demonstrate a Product-Mindful Approach
Familiarise yourself with the company’s products and think about how analytics can enhance user experience and business value. Be ready to discuss metrics that matter and how you would define KPIs that reflect real user engagement.