Senior Data Engineer: dbt, Snowflake & AWS

Delivery Centric Pty Ltd; Sydney; On-site; AUD 140,000 - 180,000; Full time

Job summary

Delivery Centric Pty Ltd is seeking an experienced Senior Data Engineer in Sydney to build scalable data pipelines using dbt, Snowflake, and AWS. The role focuses on governed, consumer-ready datasets, data workflows, and high data quality across financial pipelines.

The candidate will develop and maintain dbt models, write Snowflake SQL, and implement Airflow DAGs on AWS. Involves data model alignment, data sharing, and production lifecycle tasks.

Qualifications

• Experience with dbt Core and Snowflake SQL.
• Experience with Apache Airflow DAGs.
• Experience with AWS services (S3, Lambda, MWAA, ECS, Glue Data Catalog, Lake Formation, SQS, EventBridge).
• Experience with CI/CD pipelines using GitHub Actions.
• Experience working with fixed-format or structured financial data.

Responsibilities

• Build and maintain dbt transformation models across pipeline layers.
• Write Snowflake SQL for complex transformations and incremental loads.
• Develop and debug Apache Airflow DAGs running on AWS ECS.
• Support Python-based AWS Lambda ingestion processes and S3 event handling.
• Maintain source-to-target mapping documentation and align data models with requirements.
• Support data-sharing workflows and event-driven notifications for consumers.
• Participate in code reviews and develop YAML-based data quality tests.

Skills

dbt Core

Snowflake

SQL

Fixed-format data

Tools

Apache Airflow

AWS services (S3, Lambda, MWAA, ECS, Glue Data Catalog, Lake Formation, SQS, EventBridge)

CI/CD with GitHub Actions

Job description

Delivery Centric Pty Ltd is seeking an experienced Senior Data Engineer in Sydney to build scalable data pipelines using dbt, Snowflake, and AWS. The role focuses on governed, consumer-ready datasets, data workflows, and high data quality across financial pipelines.

The candidate will develop and maintain dbt models, write Snowflake SQL, and implement Airflow DAGs on AWS. Involves data model alignment, data sharing, and production lifecycle tasks.