About the role
This AWS Data Engineer role involves designing, building, and maintaining scalable data pipelines and analytics platforms within EY's AI & Data consulting practice. The position focuses on transforming raw data into analytics-ready datasets using a variety of AWS services to support advanced reporting and machine learning use cases.
ConsultingOnsite
Key Responsibilities
- Design and develop end-to-end data pipelines (batch and near-real-time)
- Ingest data from multiple sources (databases, APIs, applications, third-party systems)
- Transform, clean, and curate data for analytics and reporting use cases
- Build and manage data lakes and warehouses using S3, Glue, Athena, Redshift
- Develop ETL/ELT workflows using Glue, Lambda, and orchestration tools
- Ensure data quality, reliability, and scalability of pipelines
- Optimize data models, partitioning, and query performance
- Improve pipeline efficiency and manage cloud cost usage
- Monitor data jobs and resolve failures proactively
- Implement data access controls using IAM
Requirements
- Minimally 3 years' experience in data engineering (AWS)
- Bachelor's degree in computer science, Engineering, or related field
- Strong experience with AWS data services (S3, Glue, Athena, Redshift)
- Proficiency in SQL and Python
- Experience building and maintaining production data pipelines
- Understanding of data modelling (star/snowflake schemas)
- Streaming experience (Kinesis, Kafka)
- Workflow orchestration (Airflow, Step Functions)
- Infrastructure as Code (Terraform / CloudFormation)
- Exposure to BI tools (Power BI, Tableau, QuickSight)
- Highly motivated individuals with excellent problem-solving skills and the ability to prioritize shifting workloads
- An effective communicator, you'll be a confident leader equipped with strong people management skills