Senior Data Engineer

TL;DR

Senior Data Engineer (pricing/underwriting): Shaping the architecture of data products for data analytics and data science with an accent on forecasting, feature engineering, customer behaviour, and integration of new data sources. Focus on leading data transformation best practices in data modelling, performance optimisation, and data governance, building reusable technology for data ingestion, storage, transformation, and serving.

Location: London, United Kingdom (full remote available, work from home, office, or hybrid mix; work from anywhere up to 30 days/year)

Company

Online motor insurance provider using data and tech, number one in Italy with over 5 million drivers, expanding to UK and Spain.

What you will do

• Shape architecture of data products for analytics and data science use cases like forecasting, feature engineering, and new data sources.
• Lead data transformation with best practices in data modelling, performance optimisation, and data governance for consistent, reliable data.
• Build reusable technology for teams to ingest, store, transform, and serve data products.
• Engage with data scientists and ML engineers to refine data requirements and enhance infrastructure.
• Embrace continuous learning, experiment with open source tools, and participate in community activities.

Requirements

• Expert in batch/distributed processing and streaming pipelines with Kafka, Flink, Spark (Databricks plus).
• Experience implementing Data Lake/Big Data platforms with cloud (AWS preferred).
• Proficient in Python and software engineering best practices.
• Expertise in RDBMS, data warehousing, data modelling with SQL (Redshift, PostgreSQL) and NoSQL.
• Proficiency in DevOps, CI/CD, and IaC deployment best practices.

Nice to have

• Hands-on Data Quality and Data Governance.
• MLOps and feature engineering knowledge.
• Exposure to scikit-learn, pandas, NumPy, XGBoost, LightGBM.
• Apache Oozie, Apache Airflow.

Culture & Benefits

• Full flexibility: remote, office, hybrid; work from anywhere up to 30 days/year.
• Learning resources, mentorship, tailored growth plan.
• Private healthcare, gym discounts, wellbeing programs, mental health support.