Data Engineer

SKL Technology; Sydney; Hybrid; AUD 120,000 - 180,000; Full time

Job summary

SKL Technology in Sydney is seeking a hands-on Data Engineer to help build a modern cloud data platform. You’ll work across Snowflake, dbt and Azure Data Factory, focusing on pipelines, data models and improving data quality for reporting and analytics.

Join a growing Data & Insights team shaping the platform as it evolves, with opportunities to influence architecture and data standards while delivering practical data solutions for business stakeholders.

Qualifications

• Commercial experience as a Data Engineer.
• Strong hands-on Snowflake experience.
• Experience building and supporting production data pipelines.
• Good understanding of dimensional modelling and modern data warehouse design.
• Experience working with data quality issues across multiple source systems.

Responsibilities

• Build and maintain ELT pipelines into Snowflake.
• Develop, test and maintain dbt models.
• Build and manage ingestion and orchestration pipelines using Azure Data Factory.
• Create well-structured, analytics-ready datasets.
• Design dimensional models to support reporting and analytics.
• Work with data from operational, digital and legacy source systems.
• Investigate and resolve data quality issues such as duplicates, inconsistent keys and incomplete records.
• Support Power BI reporting through well-modelled and high-performing datasets.
• Work with business and data stakeholders to turn requirements into practical data solutions.
• Apply good engineering practices across Git, testing, CI/CD, code review and documentation.
• Contribute to the ongoing development of data standards, governance and platform practices.

Skills

Data engineering

Snowflake

ELT pipelines

Dimensional modelling

Data quality

Tools

dbt

Azure Data Factory

Power BI

Job description

• Sydney | Hybrid
• Permanent Role

The Opportunity

We’re looking for an experienced Data Engineer to join a growing Data & Insights team and help build out a modern cloud data platform.

This is a hands‑on role working across Snowflake, dbt and Azure Data Factory, with a strong focus on building pipelines, developing data models and improving the quality and usability of data across the business.

You’ll be joining while the platform is still evolving, so there’s plenty of opportunity to contribute to how things are built rather than stepping into a purely maintenance‑focused role.

If you enjoy building data solutions, working through complex source data and seeing your work used across reporting and analytics, this should be a good fit.

What You’ll Be Working On

• Build and maintain ELT pipelines into Snowflake.
• Develop, test and maintain dbt models.
• Build and manage ingestion and orchestration pipelines using Azure Data Factory.
• Create well‑structured, analytics‑ready datasets.
• Design dimensional models to support reporting and analytics.
• Work with data from operational, digital and legacy source systems.
• Investigate and resolve data quality issues such as duplicates, inconsistent keys and incomplete records.
• Support Power BI reporting through well‑modelled and high‑performing datasets.
• Work with business and data stakeholders to turn requirements into practical data solutions.
• Apply good engineering practices across Git, testing, CI/CD, code review and documentation.
• Contribute to the ongoing development of data standards, governance and platform practices.

What We’re Looking For

The key requirements for this role are:

• Commercial experience working as a Data Engineer.
• Strong hands‑on Snowflake experience.
• Experience building and supporting production data pipelines.
• Good understanding of dimensional modelling and modern data warehouse design.
• Experience working with data quality issues across multiple source systems.

You’ll need to be comfortable working independently, taking ownership of your work and operating in an environment where the data platform is still being developed.

Nice to Have

Experience in any of the following would be useful, but isn’t essential:

• Python.
• Power BI.
• Master data management or entity resolution.
• Customer matching or deduplication.
• iPaaS or integration platforms.
• AS400/iSeries or other legacy environments.
• Snowpark.
• ERP, ecommerce or high‑volume transactional data.
• Exposure to AI, automation or data governance initiatives.

Why Consider This Role?

This role offers a good balance between established technology and greenfield development.

You’ll be working with a modern Snowflake, dbt and Azure stack, while still having the opportunity to improve existing processes, build new pipelines and help shape how the data platform develops.

You’ll be part of a small, collaborative team where you can take ownership of your work, work directly with key stakeholders and see the impact of what you deliver.

If you’re a hands‑on Data Engineer with strong Snowflake, dbt and Azure Data Factory experience and you’re looking for your next Sydney‑based opportunity, we’d be keen to hear from you.