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DBT Data Engineer

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Summary

Data engineer in Sydney building and maintaining dbt transformation models and Snowflake SQL pipelines, orchestrating workflows with Apache Airflow on AWS ECS, and developing Python Lambda-based ingestion across AWS services like S3, Glue, and EventBridge.

  • Building and maintaining dbt transformation models across multiple pipeline layers — from raw ingestion through to governed, consumer-ready datasets
  • Writing Snowflake SQL for complex transformations: type casting, deduplication, incremental load logic, surrogate key generation
  • Developing and debugging Apache Airflow DAGs on AWS ECS
  • Contributing to AWS Lambda-based ingestion( Python) — file validation, control file generation, S3 event handling
  • Maintaining source-to-target mapping documentation and aligning models to business requirements and data specs
  • Supporting onboarding of downstream consumers via data sharing mechanisms and event-driven notifications
  • Participating in code reviews, writing YAML-based data quality tests, and owning tickets from design through to production
  • Proficiency with dbt Core (Must have)
  • Apache Iceberg Table format (Nice to have)
  • AWS - Working Knowledge of S3, Lambda, MWAA, ECS, Glue Catalogs, Lake Formation, Lambda, SQS, EventBridge
  • Experience with fixed-format or structured financial data files
  • CICD with Github Actions.

Confidentiality is assured, and only shortlisted candidates will be notified for interviews.

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See also

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