Data Engineer (DBT + Snowflake)

CareCone Group; Sydney; Presencial; AUD 150.000 - 195.000; Jornada completa

Descripción de la vacante

CareCone Group in Sydney is seeking a Senior Data Engineer to lead the data engineering strategy and platform design. You will mentor engineers, drive ingestion pipelines, and collaborate across teams to deliver reusable data products.

The role requires hands-on experience with SQL, Python, ETL/ELT, and cloud platforms, with 7+ years in data engineering and a solutions-focused mindset. On-site role in Sydney with opportunities to influence data strategy.

Formación

• University degree in a quantitative field or equivalent experience.
• 7+ years of hands-on data engineering experience.
• Advanced SQL and Python knowledge.
• ETL/ELT platforms and dimensional modelling experience (Data Lakes, Data Warehousing, Star Schema).
• Experience with one or more major cloud providers (AWS, GCP, Azure).
• Nice to have: modern data stack (dbt, Snowflake/Databricks, Airflow).
• Nice to have: software engineering, MLOps, DevOps experience (CICD, Source Control, Java, Terraform).
• Solutions mindset with curiosity to solve complex problems.

Responsabilidades

• Lead data engineering platform design and implementation.
• Mentor and inspire engineers across the business.
• Drive hands-on data ingestion and transformation pipelines for a single source of truth.

Conocimientos

Advanced SQL

Python

ETL/ELT pipelines

Data modelling

Big data concepts

Educación

Bachelor's degree in a quantitative discipline

Herramientas

AWS

GCP

Azure

dbt

Airflow

Snowflake

Databricks

Fivetran

Airbyte

Java

Terraform

Descripción del empleo

• Be the team’s “Bar Raiser”. Mentor and inspire other engineers across the business.
• Lead our Data Engineering strategy implementation, in partnership with the Head of Data Engineering.
• Lead the design and implementation of a high-performing data engineering platform.
• Lead the hands-on data ingestion and transformation pipeline build, patterns and practices to deliver a single source of truth platform of reusable data products.
• Contribute to our data product roadmap.
• Contribute to and implement data engineering continuous improvement opportunities and best practices, and team-wide ways-of-working.
• Lead technical collaborations with the other engineering and IT teams to ensure the delivery of reusable data products to the business.
• Support the infrastructure teams to ensure end-to-end delivery of data engineering services.
• Support business as usual (BAU) data products and platforms to ensure security, operationalisation, availability, reliability, and maintainability.
• Support the Governance & Risk teams to ensure we are effectively managing the risk of our data products.
• Partner closely with peers and stakeholders: Data Engineers, ML Engineers, Data Scientists, Analysts, Business Partners, Platform/DevOps Engineers, Project Managers/Scrum Masters, Testers and other business stakeholders as required.
• Support the overall Data & Analytics Centre of Excellence strategy and its execution.
• Collaborate to create outstanding people experiences for the data and analytics teams.

What we are looking for

• University degree in a quantitative discipline, such as computer science, engineering, IT, or math, or equivalent experience.
• At least 7 years of hands-on data engineering experience.
• Advanced SQL and Python knowledge.
• Hands-on ETL/ELT platforms and dimension modelling experience (e.g. Data Lakes, Data Warehousing, Star Schema, Change Data Capture, Orchestration, PII protection).
• Experience with one or more of the major cloud providers (e.g. AWS, GCP, Azure).
• Ideal, but not required: Modern data stack experience (e.g. dbt, Snowflake/Databricks, Airflow, Fivetran/Airbyte).
• Ideal, but not required: Software engineering, MLOps, DevOps experience (e.g. CICD, Source Control, Java, Terraform).
• A “solutions mindset” of natural curiosity and a strong motivation to solve problems, no matter how complicated or ambiguous they might be.