Job Description

Responsibilitiesn

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- Building and maintaining dbt transformation models across multiple pipeline layers — from raw ingestion through to governed, consumer-ready datasets
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- Writing Snowflake SQL for complex transformations: type casting, deduplication, incremental load logic, surrogate key generation
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- Developing and debugging Apache Airflow DAGs on AWS ECS
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- Contributing to AWS Lambda-based ingestion( Python) — file validation, control file generation, S3 event handling
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- Maintaining source-to-target mapping documentation and aligning models to business requirements and data specs
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- Supporting onboarding of downstream consumers via data sharing mechanisms and event-driven notifications
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- Participating in code reviews,



writing YAML-based data quality tests, and owning tickets from design through to production
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Tech stack requirednn
- Robust SQL
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- Proficiency with dbt Core (Must have)
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- Apache Iceberg Table format (Nice to have)
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- Apache Airflow
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- AWS -Working Knowledge of S3, Lambda, MWAA, ECS, Glue Catalogs, Lake Formation, Lambda, SQS, EventBridge
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- Experience with fixed-format or structured financial data files
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- CICD with Github Actions.
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Confidentiality is assured, and only shortlisted candidates will be notified for interviews

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📌 Staff Data Engineer (Sydney)
🏢 Recruit CRM
📍 Sydney