Manage data engineering projects, ensuring alignment with business objectives.
Provide strategic guidance on data engineering best practices.
Oversee a team of data engineers.
Ensure continuous improvement of data processes.
Design, develop, and maintain scalable ETL processes using Python and related data frameworks.
Build pipelines to ingest, transform, and validate data from various internal and external sources.
Ensure data quality, completeness, and integrity across all stages of the pipeline.
Optimize existing ETL jobs for better performance and reliability.
Identify manual, repetitive processes within actuarial and analytics teams and automate them using Python, APIs, or workflow orchestration tools.
Develop scripts and automation tools to streamline reporting, data validation, and data preparation tasks.

Graduate in Mathematics, Statistics, Data Science, or a related field.
2-3 years of experience in data engineering, analytics, and automation using python.
Experience with github.

Lead Assistant Manager – Business Analytics, ETL Engineer

Key skills