Data Architect

Summary :

The role involves guiding and deploying solutions for customers pertaining to the structure, integration, monitoring, storage, and governance of data. Candidates should possess experience in creating data pipelines and flows between business applications and data repositories. Technical and business acumen, particularly concerning industry-leading deployments of Data Lakes, Data Warehouses, Data Marts, and the progression of data from raw / bronze to curated / gold environments, is essential. Expertise in high transaction volume deployments is mandatory. Additionally, an understanding of Data Modeling, tabular object model, or semantic layer development, as well as Microsoft Power BI capabilities, is advantageous.

The role also involves serving as an advisor and partner in the deployment of business applications and managing migrations / integrations with other business systems. Candidates must be self-directed and capable of influencing and leading key SME teams to meet the data needs of various customer types, teams, systems, and products. Exceptional written and verbal communication skills are required, along with the ability to confidently present and defend assessments, designs, approaches, and technology decisions. A natural curiosity and a focus on technology are vital for success.

This exciting opportunity involves playing a crucial role in leveraging data to drive innovation. Collaboration with business stakeholders and data scientists to design, develop, and implement efficient and scalable data pipelines is essential.

Responsibilities :

• Collaborate with business stakeholders to comprehend their data requirements and identify high-impact use cases for data.
• Design, develop, and implement efficient and scalable data pipelines utilizing Enterprise Data Platforms.
• Construct robust and reusable data pipelines that comply with best practices and coding standards.
• Work with data scientists to prepare data for machine learning models. Create and integrate Python scripts and SQL queries for data analysis. Use tools like AWS, S3, Azure Data Bricks, and other cloud platforms for data storage and integration.
• Monitor and maintain data pipelines, addressing issues as they arise.
• Document pipelines and processes for effective communication and knowledge sharing.

Qualifications :

Preferred :