At a Glance
- Tasks: Design and develop analytical data models for AI/ML readiness and support real-time decision making.
- Company: Simply Business, a dynamic company transforming small business insurance with a focus on simplicity and value.
- Benefits: Flexible work, continuous learning, and a supportive team environment.
- Other info: Autonomous role with opportunities to mentor and drive best practices in data governance.
- Why this job: Join a mission-driven team and make a real impact on small businesses across the UK and US.
- Qualifications: 3+ years in analytics or data engineering, experience with cloud data warehouses and ML features.
The predicted salary is between 60000 - 80000 £ per year.
Simply Business is a small company with a big idea to transform the way that small businesses get the insurance they need. The aim is to reduce time, hassle and jargon while offering simplicity, choice and value; protecting livelihoods and delivering positive service from happy people, with flexible work and continuous learning. As we grow, we stay true to this focus and continue supporting our 800-strong team and 3.5 million customers. We help small businesses across the UK and the US, from barbers to bakers, consultants to cleaners—the backbone of the economy—so their dreams can grow alongside ours.
This role sits within the global Data and Analytics team (DNA). DNA has empowered data-driven decision making at Simply Business, with investments in data pipelines, data engineering, business intelligence and machine learning capabilities. The Senior Analytics Engineer is a senior technical role responsible for the design and development of robust analytical data models that act as the authoritative source of truth, feeding systems across Finance, Operations, Marketing and Enterprise Analytics. A key responsibility is pioneering AI/ML readiness by championing scalable feature sets and designing low-latency, event-driven data models to support real-time decisions (e.g., dynamic pricing, risk assessment) from quote to claims. The role operates with autonomy and requires technical expertise, strategic thinking, and the ability to set technical standards, mentor junior engineers, and drive best practices in data governance, quality assurance and documentation.
Responsibilities
- Design and build the data models in our data warehouse, ensuring they are AI and ML ready
- Integrate new sources of data to enrich our analytical capabilities and provide the necessary datasets for AI/ML models
- Work with various business and engineering teams to ensure reliable, scalable, robust architecture for our analytics platform, with a focus on feature engineering pipelines
- Manage our ELT pipelines that feed reporting systems and analytical teams
- Work with the engineering and product teams to ensure application design accommodates reporting and analytics requirements, particularly for AI and ML features
Qualifications
- 3+ years of analytics or data engineering experience
- Experience modeling and transforming data using tooling such as dbt
- Experience with cloud data warehouses such as Snowflake or Databricks
- Experience in building ML features
- Any experience in real time streaming tools and frameworks, e.g. Apache Flink, is a plus
- Any experience evaluating new tools and processes to drive the adoption and usability of AI and ML ready data
- Familiarity with a variety of programming languages
- Knowledge of the insurance domain will be an added bonus
