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. Required Skills: 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. Preferred Skills: 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. Certifications: Databricks Certification or other relevant data engineering certifications are a plus. #J-18808-Ljbffr Compunnel, Inc.
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