Data Engineer
- Compensation
- Not disclosed
- Location
- London, United Kingdom
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- batch processing
- distributed data processing
- Experience with technologies such as: Kafka Flink Spark
- Databricks experience is a plus
- Experience implementing: Data Lakes Big Data Analytics platforms
- Cloud-based solutions experience
- AWS preferred
Nice to have
- Hands-on experience with: Data Quality Data Governance techniques
- Knowledge of: MLOps Feature Engineering
- Exposure to data analysis and ML tools such as: scikit-learn pandas NumPy XGBoost LightGBM
- Familiarity with orchestration tools: Apache Oozie Apache Airflow
Full description
Fancy helping us shape the future of motor insurance? Prima could be the place for you.
Since 2015, we’ve been using our love of data and tech to rethink motor insurance and bring drivers a great experience at a great price. Our story began in Italy, where we’ve quickly become the number one online motor insurance provider. In fact, we’re trusted by over 5 million drivers. And now we’re expanding to help millions more drivers in the UK and Spain.
To help fuel that growth, we need a Senior Data Engineer to join our Engineering team.
This team is the beating heart of Prima.
You’ll be joining over 350 engineers across software development, infrastructure, operations, and security. Fueled by curiosity, experimentation, and collaboration, you’ll help deliver scalable, impactful solutions that shape the future of insurance.
Excited to make an impact? Here are the details
You’ll be joining our Pricing and Underwriting domain to bridge the gap between machine learning/data science and engineering. You will help build, publish, and maintain our complex data products and pipelines — key elements with a significant impact on the company’s growth.
What you’ll do
- Shape the architecture of data products designed for:
- data analytics
- forecasting
- feature engineering
- customer behavior analysis
- integration of new data sources
Data Transformation & Governance
- Lead best practices in:
- data modelling
- performance optimization
- data governance
- consistent
- available
- reliable
- Build reusable technology enabling teams to:
- ingest data
- store data
- transform data
- serve their own data products
Collaboration & Product Thinking
- Work closely with:
- data scientists
- machine learning engineers
- Refine data requirements and evolve infrastructure capabilities
- Stay updated with emerging technologies
- Experiment with open source tools
- Participate in community-building initiatives such as meetups