[Full Remote] Data Engineer (Pricing & Underwriting) Lazio

[Full Remote] Data Engineer (Pricing & Underwriting)
Roma
Lazio, Lazio

You'll be joining our pricing and underwriting domain to bridge the gap between machine learning/data science and engineering. With a focus on data challenges, you'll be joining forces with data scientists and machine learning engineers to craft technical solutions tailored to real-world business opportunities, drive transformative solutions, and play a pivotal role in shaping the future with us.

You will have the opportunity to work in areas like Data Architecture, Feature Engineering, Optimisation and Data Governance applying your Data Engineering industry expertise and proficiencies to tailor them to Prima's specific scenarios and innovating when faced with gaps in existing knowledge.

As a Data Engineer, you will be in charge of: Shaping the architecture of data products designed for data analytics and data science specifically focusing on use cases like forecasting, feature engineering, customer behaviour, and integration of new data sources. Leading the way in data transformation by setting up best practices in areas like Data modelling, performance optimisation, Data Governance etc, ensuring that the data used within Prima is consistent, available and reliable. Build reusable technology that enables teams to ingest, store, transform, and serve their own data products. Engaging with data scientists and machine learning engineers to explore the product landscape and refine data requirements for enhanced data infrastructure. Embrace continuous learning and experimentation to stay updated on emerging technologies, from testing open source tools to engaging in community-building activities like Meetups. Your passion for staying at the forefront of the field will drive your journey. Requirements: Expert in batch, distributed data processing and near real-time streaming data pipelines with technologies like Kafka, Flink, Spark etc. Experience in Databricks is a plus. Experience in Data Lake / Big Data Analytics platform implementation with cloud based solution; AWS preferred. Proficient in Python programming and software engineering best practices. Expertise with RDBMS, Data Warehousing, Data Modelling with relational SQL (Redshift, PostgreSQL) and NoSQL databases. Proficiency in DevOps, CI/CD pipeline management, and expertise in infrastructure as Code (IaC) deployment industry-best practices. Nice to have: Hands-on experience in Data Quality and Data Governance techniques. Knowledge on MLOps and Feature engineering. Exposure to common data analysis and ML technologies such as on scikit-learn, pandas, NumPy, XGBoost, LightGBM. Exposure to tools like Apache Oozie, Apache Airflow.

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