Senior Data Engineer - Snowflake Migration & MLOps
- Key role in Databricks to Snowflake migration
- Build scalable data platforms and support analytical workloads
- Operationalise machine learning solutions within AWS
This role will play a key part in a major Databricks to Snowflake migration, helping modernise the organisation's data and machine learning capabilities. You'll work closely with Data Engineers, Data Scientists, Platform Engineers, Architects, and business stakeholders to build scalable data platforms, support analytical workloads, and operationalise machine learning solutions within AWS.
This is a hands-on role suited to someone who enjoys working across both Data Engineering and MLOps disciplines and wants to be part of a large-scale cloud transformation program.=
Essential Skills & Experience
- Strong experience working as a Data Engineer within enterprise environments
- Hands-on experience with Databricks
- Hands-on experience with Snowflake
- Strong SQL and Python development skills
- Strong experience building and maintaining modern data pipelines and data platforms
- Experience with dbt
- Experience working within AWS environments
- Experience supporting MLOps or Machine Learning platforms in production environments
- Exposure to machine learning lifecycle activities such as model deployment, monitoring, operationalisation, or supporting Data Science teams
- Strong understanding of data modelling, data warehousing, cloud-native architecture, and modern data engineering practices
- Experience working across both technical and business stakeholder groups
- Strong problem-solving, communication, and collaboration skills
Desirable Skills
- Experience with Apache Airflow
- Experience with Spark / PySpark
- Experience with MLflow or similar machine learning lifecycle tools
- Experience with Infrastructure as Code tools such as Terraform
- Experience with GitHub Actions, Jenkins, Azure DevOps, or similar CI/CD tooling
- Experience supporting analytics, AI, or advanced machine learning initiatives
About You
You enjoy solving complex data challenges and understand that great data platforms underpin successful analytics and machine learning outcomes.
You're comfortable working across engineering, data, and stakeholder-facing activities and can confidently bridge the gap between technical implementation and business value. You enjoy modern cloud technologies, collaborative delivery environments, and take pride in building scalable, reliable data solutions.
How to Apply
Interested candidates may apply directly via the advertisement or forward their resume and a brief suitability statement outlining their experience with Databricks, Snowflake, dbt, AWS, and MLOps to: mnarciso@4impact.com.au
Applications that clearly demonstrate relevant Snowflake migration, Data Engineering, and MLOps experience will be highly regarded.
This role will play a key part in a major Databricks to Snowflake migration, helping modernise the organisation's data and machine learning capabilities. You'll work closely with Data Engineers, Data Scientists, Platform Engineers, Architects, and business stakeholders to build scalable data platforms, support analytical workloads, and operationalise machine learning solutions within AWS.
This is a hands-on role suited to someone who enjoys working across both Data Engineering and MLOps disciplines and wants to be part of a large-scale cloud transformation program.=
Essential Skills & Experience
- Strong experience working as a Data Engineer within enterprise environments
- Hands-on experience with Databricks
- Hands-on experience with Snowflake
- Strong SQL and Python development skills
- Strong experience building and maintaining modern data pipelines and data platforms
- Experience with dbt
- Experience working within AWS environments
- Experience supporting MLOps or Machine Learning platforms in production environments
- Exposure to machine learning lifecycle activities such as model deployment, monitoring, operationalisation, or supporting Data Science teams
- Strong understanding of data modelling, data warehousing, cloud-native architecture, and modern data engineering practices
- Experience working across both technical and business stakeholder groups
- Strong problem-solving, communication, and collaboration skills
Desirable Skills
- Experience with Apache Airflow
- Experience with Spark / PySpark
- Experience with MLflow or similar machine learning lifecycle tools
- Experience with Infrastructure as Code tools such as Terraform
- Experience with GitHub Actions, Jenkins, Azure DevOps, or similar CI/CD tooling
- Experience supporting analytics, AI, or advanced machine learning initiatives
About You
You enjoy solving complex data challenges and understand that great data platforms underpin successful analytics and machine learning outcomes.
You're comfortable working across engineering, data, and stakeholder-facing activities and can confidently bridge the gap between technical implementation and business value. You enjoy modern cloud technologies, collaborative delivery environments, and take pride in building scalable, reliable data solutions.
How to Apply
Interested candidates may apply directly via the advertisement or forward their resume and a brief suitability statement outlining their experience with Databricks, Snowflake, dbt, AWS, and MLOps to: mnarciso@4impact.com.au
Applications that clearly demonstrate relevant Snowflake migration, Data Engineering, and MLOps experience will be highly regarded.
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