Cloud Data Engineer

1 Day ago • 8 Years + • Data Analysis

Job Summary

Job Description

Support one of the top Australian banks in modernizing their data and analytics platform. You will work directly with IT and business stakeholders in the Data and Platform team to implement the bank's data strategy to become the world's best AI bank. Responsibilities include creating technology blueprints and engineering roadmaps for multi-year data transformational programs, demonstrating knowledge of architectural patterns, cloud-native solutions on AWS, microservices architecture, solutions integration, and containerization. You will leverage extensive knowledge of AWS services, particularly those related to data storage and processing like S3, RDS, Redshift, DataZone, and Glue. Expertise in the data development lifecycle is crucial, focusing on data ingestion processes, data transformation pipelines, data integration, and visualization. Excellent stakeholder management skills and a 'Can-do' attitude are essential.
Must have:
  • 8+ years of hands-on experience as AWS Platform Engineer
  • Hands-on experience in AWS compute and services including EC2
  • 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)
Good to have:
  • AWS Solution Architect certification
  • Containerization (Docker, Kubernetes)
  • Data visualization 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

Job Details

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
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Create technology blueprints and engineering roadmaps for multi-year data transformational programs.

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knowledgeable of architectural patterns, cloud-native solutions on AWS, microservices architecture, solutions integration and containerisation.

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Extensive knowledge of AWS services, particularly those related to data storage and processing, including S3, RDS, Redshift, DataZone and Glue.

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Expert in the data development lifecycle, with a focus on data ingestion processes, data transformation pipelines, data integration, and visualisation.

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Excellent stakeholder management skills and 'Can-do' attitude

Skills

Must have

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8+ years of hands-on experience as AWS Platform Engineer

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Hands on experience in AWS compute and services including EC2 and experience building data technology stack incl Hadoop/EMR Serverless, Glue, Redshift, Airflow, Aurora PostgreSQL

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Worked on event driven architecture using Apache Kafka, AWS Kinesis, or similar Infrastructure as code using CloudFormation or Terraform

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Proficient in Python, SQL

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Building CI/CD tooling (Github/Jenkins)

Nice to have

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AWS Solution Architect certification

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Containerisation (Docker, Kubernetes)

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Data visualisation tools and integration to Tableau, PowerBI

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Alation

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Observability tools (i.e. Observe, Splunk or Prometheus/Grafana).

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Ab initio or DBT tooling

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Experience with Parquet File Format, Iceberg tables

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Glue Data Catalogue & AWS DataZone

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Markets domain knowledge.

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Experience dealing with complex hierarchical datasets such as those used to represent financial products in the likes of Murex/MRE/Wallstreet

Other
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Languages

English: C2 Proficient

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Seniority

Senior

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