Data Engineer

Zone IT Solutions; Western Australia; Presencial; AUD 120.000 - 160.000; Jornada completa

Descripción de la vacante

Zone IT Solutions Pty Ltd in Western Australia is seeking a seasoned Business Analyst with strong data platform, analytics, and digital-product experience to shape business outcomes and translate them into actionable requirements.

You will own data engineering tasks—designing data models with dbt, building robust Snowflake pipelines, and enabling forecasting workloads in collaboration with data scientists and analysts.

Formación

• 5+ years of data engineering experience.
• Bachelor's degree in Computer Science, Engineering, Statistics, Data Science, or related field.
• Strong problem-solving and analytical thinking.
• Ability to work with complex business and data requirements.
• Clear communication and stakeholder engagement skills.
• Ownership mindset and attention to detail.

Responsabilidades

• Design, develop, and maintain scalable data models using dbt.
• Build high-quality datasets through complex transformations, joins, and aggregations.
• Apply testing, documentation, and data quality practices to analytical assets.
• Develop and optimise SQL-based solutions within Snowflake.
• Design performant, maintainable transformation pipelines.
• Support data governance and efficient use of platform resources.
• Develop and maintain Databricks notebooks and workflow pipelines.
• Support automated forecasting using Databricks Workflows.
• Prepare datasets to support forecasting and analytics workloads.
• Collaborate with data scientists, analysts, and engineers.

Conocimientos

5+ years data engineering

Strong problem solving

Clear communication

Ownership mindset

Stakeholder engagement

Educación

Bachelor's degree in Computer Science or related

Herramientas

Snowflake

Databricks

Python

R

dbt

SQL

Descripción del empleo

Job/Project Description – tasks to be performed on a daily basis:

Role Summary

We are seeking a Business Analyst with strong experience in business transformation, data platforms, analytics, and digital products. This role is business-focused: you will shape business outcomes, translate them into clear requirements, and define the features needed to deliver value across enterprise data and analytics initiatives.

Mandatory Requirements:

Key Responsibilities

• Design, develop, and maintain scalable data models using dbt.
• Build high-quality datasets through complex transformations, joins, and aggregations.
• Apply testing, documentation, and data quality practices to analytical assets.

2. Snowflake Engineering

• Develop and optimise SQL-based solutions within Snowflake.
• Design performant, maintainable, and reliable transformation pipelines.
• Support data governance, consistency, and efficient use of platform resources.
• Develop and maintain Databricks notebooks and workflow pipelines.
• Support automated forecast execution using Databricks Workflows.
• Manage deployments using Databricks CLI and Databricks Asset Bundles (DABs).

4. Forecasting Data Enablement

• Prepare datasets that support forecasting and analytics workloads.
• Work closely with data scientists and analysts to deliver data requirements.
• Ensure forecasting inputs are accurate, trusted, and production-ready.

5. Engineering Excellence & Collaboration

• Write clean, maintainable, and well-documented code.
• Participate in code reviews and technical design discussions.
• Collaborate effectively with engineers, analysts, and data scientists.

Key Skills & Experience

• 5+ years of data engineering experience.
• Bachelor's degree in Computer Science, Engineering, Statistics, Data Science, or a related discipline.
• Strong problem-solving and analytical thinking.
• Ability to work with complex business and data requirements.
• Clear communication and stakeholder engagement skills.
• Ownership mindset and attention to detail.

Required Professional and Technical Expertise:

• Experience supporting forecasting, analytics, or data science workloads.
• Knowledge of statistical analysis, time-series data, or forecasting concepts.
• Experience with R and collaboration within data science environments.
• Knowledge of cloud-based data platforms and modern data architectures.

Desired Attributes and Skills:

Technical Skills

1. Data Platforms:

Snowflake, data warehousing, and SQL optimisation.

2. Data Transformation:

dbt, data modelling, testing, documentation, and CI/CD practices.

3. Databricks:

Databricks notebooks, Workflows, Databricks CLI, and Databricks Asset Bundles.

4. Programming:

Python and notebook-based development.

ETL/ELT concepts, pipeline development, orchestration, and data quality management.

Git, deployment automation, and software engineering best practices.