Data Modelling - Azure

Description

We are seeking a skilled Data Modelling professional with expertise in Azure Databricks, SQL, and Redshift to join our dynamic team. In this role, you will leverage your knowledge to enhance our data infrastructure and ensure efficient data processing and analysis. Your primary responsibility will be to design, implement, and optimize data models that support advanced analytics and reporting needs. You will be working closely with data engineers, analysts, and business stakeholders to understand their data requirements and translate them into effective data solutions. Your experience with Azure Databricks and Redshift will enable you to build robust data pipelines and maintain high data quality standards. Additionally, you will be expected to contribute to the design of our data architecture, ensuring it aligns with business objectives. This is an exciting opportunity for someone who is passionate about data and wants to make a significant impact on our organization's data strategy. Join us and help shape the future of data utilization at our company, driving insights that lead to better business decisions and outcomes for our clients.

Responsibilities

- Design and implement data models using Azure Databricks and Redshift.

- Collaborate with data engineers and analysts to gather data requirements.

- Develop and maintain ETL processes for data ingestion and transformation.

- Ensure data quality and integrity across all data models and pipelines.

- Optimize existing data models for performance and scalability.

- Write and maintain SQL scripts for reporting and analysis purposes.

- Document data models and processes for internal knowledge sharing.

Requirements

- Bachelor's degree in Computer Science, Information Systems, or a related field.

- Proven experience with Azure Databricks and Redshift.

- Strong proficiency in SQL and data modeling techniques.

- Experience in ETL processing and data pipeline construction.

- Familiarity with data warehousing concepts and best practices.

- Ability to effectively communicate complex data concepts to non-technical stakeholders.

- Strong analytical and problem-solving skills, with attention to detail.