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Senior Data Engineer / Data Scientist (remote)

North American Search Group

Remote

CAD 60,000 - 80,000

Full time

Yesterday
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Job summary

A leading North American recruitment agency is seeking a qualified individual to design, build, and maintain ETL/data pipelines supporting predictive models in the P&C insurance sector. The role requires a strong background in Data Engineering and Data Science, alongside hands-on experience with AWS, Airflow, Python, Pandas, and advanced SQL. The candidate will collaborate with data scientists and product managers, emphasizing quality and scalability in their data assets and code.

Qualifications

  • Strong background in Data Engineering and Data Science within P&C insurance.
  • Hands-on experience with AWS, Airflow, Python, Pandas, and advanced SQL.
  • Experience building data pipelines and features for predictive modeling.
  • Comfortable working in regulated or complex data environments.

Responsibilities

  • Design, build, and maintain ETL/data pipelines supporting predictive models in P&C insurance.
  • Perform data exploration, profiling, reconciliation, and feature engineering.
  • Partner with data scientists, actuaries, and product managers to productionize models.
  • Own data assets, datasets, and code with an emphasis on quality, scalability, and documentation.

Skills

Data Engineering
Data Science
AWS
Airflow
Python
Pandas
Advanced SQL
Job description
RESPONSIBILITIES
  • · Design, build, and maintain ETL/data pipelines supporting predictive models in P&C insurance
  • · Perform data exploration, profiling, reconciliation, and feature engineering
  • · Partner with data scientists, actuaries, and product managers to productionize models
  • · Own data assets, datasets, and code with an emphasis on quality, scalability, and documentation
QUALIFICATIONS
  • · Strong background in Data Engineering + Data Science within P&C insurance
  • · Hands-on experience with AWS, Airflow, Python, Pandas, and advanced SQL
  • · Experience building data pipelines and features for predictive modeling
  • · Comfortable working in regulated or complex data environments
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