Cloud Data Engineer
1 week ago
- Project description
Support one of the top Australian banks as they seek to modernise their data and analytics platform.
You will be working directly with IT and business stakeholders in Data and Platform team to implement banks data strategy to become the best AI bank of the world. - Responsibilities
- Create technology blueprints and engineering roadmaps for multi-year data transformational programs.
- knowledgeable of architectural patterns, cloud-native solutions on AWS, microservices architecture, solutions integration, and containerisation.
- Extensive knowledge of AWS services, particularly those related to data storage and processing, including S3, RDS, Redshift, DataZone, and Glue.
- Expert in the data development lifecycle, with a focus on data ingestion processes, data transformation pipelines, data integration, and visualisation.
- Excellent stakeholder management skills and ''Can-do'' attitude.
- Skills
Must have - 8+ years of hands-on experience as AWS Platform Engineer
- Hands-on experience in AWS compute and services, including EC2 and experience building data technology stack, including Hadoop/EMR Serverless, Glue, Redshift, Airflow, Aurora PostgreSQL
- Worked on event-driven architecture using Apache Kafka, AWS Kinesis, or similar. Infrastructure as code using CloudFormation or Terraform
- Proficient in Python, SQL
- Building CI/CD tooling (Github/Jenkins)
Nice to have
- AWS Solution Architect certification
- Containerisation (Docker, Kubernetes)
- Data visualisation tools and integration to Tableau, PowerBI
- Alation
- Observability tools (i.e., Observe, Splunk, or Prometheus/Grafana).
- Ab initio or DBT tooling
- Experience with Parquet File Format, Iceberg tables
- Glue Data Catalogue & AWS DataZone
- Markets domain knowledge
- Experience dealing with complex hierarchical datasets such as those used to represent financial products in the likes of Murex/MRE/Wallstreet
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