Analytics Engineer

• Develop and manage small statistical analysis projects.
• Ensure documentation and statistical standards are adhered to.
• Develop and deliver training sessions on statistical best practices.
• Provide feedback and support to junior team members.
• 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.
• Implement monitoring, logging, and error-handling frameworks for automated workflows.
• Support actuarial teams by preparing data for modeling, reserving, pricing, forecasting, and financial reporting.
• Build utilities to help analysts efficiently analyze large datasets.
• Assist with the production of actuarial models or dashboards where needed.
• Work with actuaries, data scientists, and business users to understand analytical requirements and translate them into technical solutions.
• Document data processes, automation logic, and technical designs for internal reference.
• Provide technical troubleshooting and support for data-related or automation issues.
• Follow best practices for Python development, version control, testing, and deployment.
• Contribute to improving data engineering standards, coding practices, and team workflows.
• Evaluate new tools, libraries, and methods to enhance data processing and automation efficiency.

Assistant Manager – Business Analytics, ETL Engineer

Analytics Engineer, E‑Commerce

BI Analytics Engineer

EDW Informatica ETL Developer

Data Analytics Engineer

Analytics Engineer