Job Description

We are looking for a skilled Data Mesh Data Modeler with expertise in Databricks to join our team. The ideal candidate will be responsible for designing and implementing scalable and efficient data models within a data mesh architecture, ensuring reliable and efficient data processing while collaborating with cross-functional teams. You will leverage Databricks for various data engineering tasks, from data processing to orchestration, to meet the needs of our data-driven organization.

Job Responsibilities:

• Design and implement scalable, efficient data models within a data mesh architecture, following principles such as domain-driven design and federated data governance.
• Work closely with data architects, engineers, and business stakeholders to translate business requirements into technical solutions.
• Communicate data model designs effectively to technical and non-technical teams.
• Leverage Databricks for data engineering tasks, including data processing, data validation, and data orchestration.
• Optimize data pipelines to ensure high performance, scalability, and efficient data processing.
• Implement data validation rules and quality checks to ensure data integrity and consistency
• Design, implement, and manage the lifecycle of data products within the Data Mesh architecture.
• Collaborate with other teams to build, manage, and monitor efficient data pipelines and data products.

• Experience in Data Mesh Architecture: Expertise in modeling data products and understanding the principles of data mesh, domain-driven design, and federated governance.
• Databricks Expertise: Strong hands-on experience with Databricks, including using Spark for large-scale data processing, validation, and orchestration.
• Programming Skills: Proficiency in SQL and Python for data processing, transformation, and validation.
• Data Pipeline Optimization: Experience in designing and optimizing data pipelines to ensure scalability, high performance, and efficient data flow.
• Data Integrity: Implementing robust data validation and quality checks to ensure data consistency and accuracy across systems.
• Collaboration: Strong ability to work closely with cross-functional teams, including business users, data architects, and engineers.
• Problem-Solving: Strong troubleshooting and problem-solving skills to ensure the efficiency and reliability of data systems.

• Experience in designing and managing the lifecycle of Data Products within a Data Mesh architecture.
• Familiarity with data governance practices and tools for managing data quality and compliance.
• Knowledge of cloud platforms like AWS, Azure, or GCP for deploying and managing data solutions.

Databricks Certification or other relevant data engineering certifications are a plus.

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