Data Engineer

• We build, optimise, and deploy price optimisation machine learning ETL/ELT pipelines and data processes.
• We improve and adapt our data infrastructure and code base as we scale, including collaboration, security, scalability, efficiency, automation, and auditability.
• We interact with new clients on client pitches and work with existing clients to onboard our software, offering engineering and pricing expertise.
• We scale our infrastructure as we take on more and larger clients.
• We streamline and automate data refresh processes.
• We improve our data security.
• We build and deploy machine learning models.
• We get involved with client pitches.
• We travel to clients occasionally.

Technologies:

• AI
• Airflow
• AWS
• Azure
• Cloud
• Docker
• ETL
• GCP
• Kubernetes
• Machine Learning
• MySQL
• Python
• PySpark
• Security
• numpy
• pandas
• Backend
• React
• jQuery

• We require a strong academic background with a minimum bachelors or masters degree in a STEM subject such as Computer Science, Mathematics, or Engineering.
• We require at least 2 years experience working as a data engineer, ideally in consulting or financial services.
• We require proficiency in Python, including pandas and numpy.
• We require professional experience with Azure cloud services; AWS or GCP experience is acceptable with deeper experience.
• We require strong experience deploying clean, maintainable, production-level code.
• We require a basic understanding of DAGs and their role in pipeline orchestration.
• We would prefer professional experience with PySpark, MySQL, Docker, and Kubernetes.
• We would prefer experience with best-practice pipeline orchestration software such as Airflow or Dagster.
• We would prefer experience migrating code from prototype notebooks to .py files while maintaining logic and transparency.
• We would prefer ownership of a project across the full software product lifecycle, from data infrastructure through model development and deployment to front-end integration.
• We would prefer experience with pricing analytics and/or optimisation, ideally in retail banking.
• We would prefer experience producing PowerPoint presentations or reports and presenting to clients or colleagues.
• We would prefer an entrepreneurial spirit and a willingness to work in an early-stage start-up where impact is directly rewarded.
• We require applicants to have the permanent right to work in the UK, as we cannot sponsor visas.

We are Clariti AI, a B2B SaaS company providing price optimisation software to retail banks. Our software helps banks make pricing decisions on products such as mortgages and savings, generating recommendations worth millions of pounds or euros in additional revenue. We are a fast-scaling, bootstrapped and profitable business with a growing client base in the UK and Ireland, and a strong pipeline of new clients. This Data Engineer role is based in London/Hybrid, with office attendance two or more days per week and occasional client travel. We offer a highly competitive salary, a compelling profit share scheme with the potential to own a significant stake in the business, equity options, flexible working hours, work-anywhere flexibility for up to two months a year, regular performance-based promotions and pay increases, and 25 days holiday increasing to 30 days over time.