About the job

About Cognizant Consulting

Cognizant Consulting is more than Cognizant’s consulting practice—we’re a global community of experts dedicated to helping clients reimagine their business. By combining deep industry knowledge with leading technology and data expertise, we design and deliver innovative solutions for some of the world’s most recognised organisations.

About The Role

As a Consulting Data & AI Engineer, you will make an impact by designing and delivering scalable, cloud-based data and AI solutions that solve complex business problems. You will be a valued member of Cognizant Consulting’s Data & AI practice, working closely with clients, architects, and cross‑functional consulting teams to translate data into actionable insights and business outcomes.

In This Role, You Will

• Design, build, and deliver enterprise-scale data engineering solutions using Snowflake, cloud platforms, and modern analytics tooling.
• Develop robust, scalable data pipelines and transformation workflows (including ETL/ELT and dbt) to enable high-quality, analytics-ready data.
• Collaborate with technical leads and architects to implement solutions using modern engineering and DevOps best practices.
• Partner with business and technology stakeholders to understand requirements and deliver outcomes aligned to client priorities.
• Contribute to solution design, technical decision-making, and continuous improvement across client engagements and the Data & AI practice.

Work model

We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a hybrid position requiring 3 days a week in a client or Cognizant office in Melbourne, VIC. Regardless of your working arrangement, we are here to support a healthy work-life balance though our various wellbeing programs.

What You Must Have To Be Considered

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related discipline.
• 3+ years’ experience in data engineering, analytics engineering, or applied Data & AI roles.
• Strong hands-on experience with Snowflake, including data modelling and performance optimisation.
• Experience building data pipelines on cloud platforms such as Azure, Azure Fabric, or AWS.
• Proficiency in SQL and Python, with experience using modern data and analytics tools (including dbt).

These will help you succeed

• Experience with distributed data platforms such as Spark or Databricks.
• Exposure to machine learning, MLOps, or AI-enabled solutions, including emerging AI technologies.
• Strong consulting mindset, with the ability to communicate complex technical concepts to non-technical stakeholders.
• Experience working in fast‑paced, client-facing environments where priorities evolve.

• Design, build, and deliver enterprise-scale data engineering solutions using Snowflake, cloud platforms, and modern analytics tooling.
• Develop robust, scalable data pipelines and transformation workflows (including ETL/ELT and dbt) to enable high-quality, analytics-ready data.
• Collaborate with technical leads and architects to implement solutions using modern engineering and DevOps best practices.
• Partner with business and technology stakeholders to understand requirements and deliver outcomes aligned to client priorities.
• Contribute to solution design, technical decision-making, and continuous improvement across client engagements and the Data & AI practice.

• Snowflake
• Cloud platforms (Azure, Azure Fabric, AWS)
• SQL
• Python
• dbt
• ETL/ELT
• DevOps best practices
• Spark
• Databricks
• Machine learning
• MLOps
• AI-enabled solutions
• Consulting mindset
• Communication skills

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related discipline.
• 3+ years’ experience in data engineering, analytics engineering, or applied Data & AI roles.
• Strong hands-on experience with Snowflake, including data modelling and performance optimisation.
• Experience building data pipelines on cloud platforms such as Azure, Azure Fabric, or AWS.
• Proficiency in SQL and Python, with experience using modern data and analytics tools (including dbt).