Staff Data Engineer

Tech Aalto Pte ltd; Sydney; On-site; AUD 120,000 - 160,000; Full time

Job summary

Recruit CRM in Sydney is seeking a data engineer to build and maintain dbt models across multiple pipeline layers, from raw ingestion to governed datasets. The role emphasizes Snowflake SQL, complex transformations, and robust data quality checks.

You will develop Airflow DAGs on AWS ECS, and contribute to Python-based ingestion using Lambda functions, with strong emphasis on data sharing and production readiness. A hands-on, collaborative environment awaits.

Qualifications

• Strong SQL experience.
• Proficiency with dbt Core (Must have).
• Experience with Snowflake SQL for transformations.
• Experience with Apache Airflow.
• AWS knowledge across S3, Lambda, MWAA, ECS, Glue Catalogs and Lake Formation.
• Experience handling fixed-format or structured data files.
• CI/CD with GitHub Actions.

Responsibilities

• Building and maintaining dbt transformation models from raw ingestion to governed data sets.
• Writing Snowflake SQL for complex transformations including type casting, deduplication, and surrogate keys.
• Developing and debugging Apache Airflow DAGs on AWS ECS.
• Contributing to AWS Lambda-based ingestion in Python including file validation and S3 events.
• Maintaining source-to-target mapping and aligning models to data specs.
• Supporting onboarding of downstream consumers via data sharing and event-driven notifications.
• Participating in code reviews, writing YAML-based data quality tests, and owning tickets end-to-end.

Skills

SQL

dbt Core

Snowflake SQL

Airflow

AWS

Python

Data validation

GitHub Actions

Data modeling

Tools

Snowflake

Apache Airflow

S3

Lambda

MWAA

ECS

Glue Catalogs

Lake Formation

EventBridge

Apache Iceberg

SQS

Job description

Responsibilities

• 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

Tech stack required

• Strong SQL
• Proficiency with dbt Core (Must have)
• Apache Iceberg Table format (Nice to have)
• Apache Airflow
• 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