Data Engineer
Permanent
Location: Remote working with some onsite working
Salary: Up to £75K

Skills: SQL, Power BI, ETL, SSIS, Data Factory, Azure

We are looking to recruit an SC Cleared Data Engineer for a leading software & solutions organisation. The Data Engineer will design, develop and maintain robust data infrastructure and ETL pipelines that support the data needs of projects, services and customers. To create insightful data visualisations and dashboards in PowerBI to enable data-driven decision-making. Collaborate with Data Consultants, Architects and other professionals to offer seamless and effective data solutions to customers.

Due to the nature of the work valid SC Clearance is essential.

Key Responsibilities:

Build data pipelines for data throughout the Azure Data Platform stages, integrating data management best practices at all stage transitions suitable for their use case, e.g., reporting, or archival of data from operational systems or unstructured data stores
Strong proficiency in SQL and SSIS for ETL processes.
Experience in Azure data platforms, including Azure Data Factory, Azure SQL Database, Fabric.
Experience in designing and building data warehouses.
Advanced skills in Power BI for data visualization and reporting.
Knowledge of data modeling, data warehousing concepts, and ETL best practices.
Design and implement data integrations between data platforms and operational systems both on premises and in the cloud
Develop data sets which are optimised for their given use case, e.g., self-service analytics, paginated reports or machine learning and advanced analytics
Migrate data from legacy reporting solutions on the azure data platforms to ensuring that data integrity and service levels are maintainedEssential Skills:

SQL including T-SQL (Queries, views, stored procedures, functions)
Microsoft BI experience / Data visualisation (SSAS, SSRS, Power BI)
Integration and ETL design and delivery Including (SSIS, Azure Data Factory)
Azure Data Services (including Data Factory, Databricks, Synapse Analytics, Data Lake)
Relational and multi-dimensional data modelling
Designing and delivering Testing including Regression, Unit, integration, and system for data solutions
Understanding of industry best practice and trends together with their application within a business context
Broad knowledge of the financial services industry and key regulatory requirements together with an understanding of business processes
Strong understanding of data management and data governance best practices
Experience in defining and delivering solutions to handle sensitive data including data obfuscation, cascade deletion of data, anonymisation