As a Lead Data Engineer, you will play a crucial role in designing, developing, and maintaining our data infrastructure. You will lead a team of data engineers to ensure the successful delivery of projects and contribute to the overall data strategy. The ideal candidate will have extensive experience in cloud-based data technologies, particularly in Azure, and a proven track record of implementing scalable and efficient data solutions.
Responsibilities:
The Lead Data Engineer is responsible for overseeing the data warehouse implementation, ensuring that data practices align with the strategic goals of wealth and asset management services.
The role involves managing data analytics and data warehousing projects, developing, and implementing data models, and leading a team of data Analysts.
Design and implement comprehensive data strategies that enhance decision-making capabilities across wealth and asset management portfolios.
Lead the development and maintenance of scalable data models and databases within a modern EDW.
Ensure data integrity, quality, and compliance with industry regulations.
Create high-level conceptual data models that define the essential entities and their relationships, capturing the broad scope of the organization's data landscape.
Translate conceptual models into logical data models that detail the structure of the data without being tied to any specific database technology. These models include attributes, keys, and the relationships between entities.
Implement logical data models into physical schemas optimized for the specific technologies used within the EDW, considering performance and storage requirements.
Utilize dimensional modelling techniques, such as star schemas and snowflake schemas, which are particularly effective for data warehousing in financial reporting and analytics.
Design fact tables and dimension tables to support the organization's business intelligence tools and data warehousing needs.
Develop and enforce data modelling standards and practices to ensure consistency and quality across the data warehouse.
Work with data governance teams to ensure that data handling meets compliance requirements and industry standards for data privacy and security.
Translate complex data findings into actionable insights and strategic recommendations.
Skills required:
Bachelor's or master's degree in computer science, Engineering, or a related field.
8 to 12 years of experience in data engineering, with a focus on Microsoft technologies.
Proficiency in Azure data services, including Azure Databricks, Azure Synapse Analytics, and Azure Data Factory.
Hands-on experience with Microsoft SQL Server Integration Services (SSIS).
Strong understanding of data modelling concepts and database design principles.
Excellent communication and leadership skills, with the ability to effectively collaborate with stakeholders at all levels.
Experience working in an Agile development environment is preferred.
Certifications in relevant technologies (e.g., Microsoft Certified: Azure Data Engineer Associate) is a plus.
Prior experience of working on Data strategy in Wealth Management industry will be a big +
Must have :
Demonstrable data modeling experience with Kimball and DataVault architectures