Develop and maintain robust and efficient data solutions and products including data transformation, data modelling, and reporting on both on-premises and cloud environments
Build modern data lake/lakehouse architectures that support scalable, flexible data processing
Enhance platform integration by leveraging domain events to enable more efficient and real-time data processing
Champion the adoption of generative AI features such as Amazon Q and Copilot to deliver intuitive analytics experiences
Build sophisticated solutions to deliver actionable insights, with a strong focus on performance, scalability, and data accessibility
Enhance data engineering processes through automation, implementing CI/CD pipelines, and optimizing ETL/ELT flows to improve efficiency and maintainability
Collaborate with cross-functional teams to translate business requirements into technical solutions, documenting them as GAPs and aligning them with Architects
Facilitate data discovery and enhance data management processes using platforms like Open Metadata
Ensure KPIs and documentation remain accurate and up to date
Support data quality and compliance standards across the organization
Initiate and experiment with new ideas and approaches that support the A&I department's strategy

5+ years of experience in data engineering
Experience building modern data lake/lakehouse architectures (e.g., Apache Iceberg) in cloud environments
Strong knowledge of AWS (S3, Redshift) or Azure data services
Experience with ETL/ELT processes and data ingestion
Proven expertise using transformation tools such as dbt
Experience with data pipeline orchestration tools (such as Apache Airflow)
Experience with best practices applied to data (e.g., testing, CI/CD)

Senior Data Engineer

Key skills