Senior Data Modeller
Capgemini Invent
Date: 16 hours ago
City: Melbourne, Victoria
Contract type: Full time

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Job Description
As a Data Modeller – Azure/Databricks, you will be able to design, implement, and optimize scalable data models for cloud-based solutions. This role involves working closely with data engineers, architects, and business stakeholders to ensure efficient data structures and seamless integration across the Azure ecosystem.
Key Responsibilities
Qualifications & Experience:
Job Description
As a Data Modeller – Azure/Databricks, you will be able to design, implement, and optimize scalable data models for cloud-based solutions. This role involves working closely with data engineers, architects, and business stakeholders to ensure efficient data structures and seamless integration across the Azure ecosystem.
Key Responsibilities
- Design and implement data models for structured and unstructured data.
- Develop and optimize data pipelines using Azure & Databricks.
- Define and enforce data governance, security, and best practices.
- Collaborate with stakeholders to translate business needs into data models.
- Support data integration, transformation, and storage strategies.
- Optimize performance and scalability of data solutions.
Qualifications & Experience:
- Bachelor's degree in Computer Science, IT, or a related field.
- Strong experience in data modeling, database design, and ETL processes.
- Proficiency in Azure services (Azure Data Lake, Synapse, Data Factory, SQL DB).
- Hands-on experience with Databricks, Delta Lake, and Apache Spark.
- Expertise in SQL, Python, or Scala for data engineering.
- Strong understanding of normalization, denormalization, and data warehousing.
- Experience with data governance, security, and compliance frameworks.
- Azure Data Engineer or Databricks certification.
- Experience with data mesh, data fabric, or lakehouse architectures.
- Familiarity with CI/CD, DevOps, and Infrastructure as Code (IaC).
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