Data Engineer (Intermediate)

Responsibilities include:

•Designing and building end to end BI solutions, that will extract data from multiple systems, transforming and loading into multiple reporting data warehouses

•Working with end users and analysts on requirements and translate them into technical specification, provides estimation to the management

•Supporting existing BI Platform, reverse engineer and improve processes

•Following and contributing to departmental development process in terms of standards, methodologies, testing, version control and documentation, drive and implement industry best practices, evaluate and introduce new tools, design and improve existing ETL framework, data validation framework

•Assist in the migration to an off-premises Cloud Solution (Specifically Microsoft Azure)

Experience, skill and capability

•3-5 years’ of Data Engineering experience

•Excellent data analysis and exploration using T-SQL, and strong SQL programming (stored procedures, functions)

•Extensive experience of using SSIS, script tasks, custom plugins

•Experience of building solutions with SSAS, advanced knowledge of SSAS, MDX, performance tuning, best practices, 2008 onwards

•Knowledge and experience of data warehouse modelling methodologies

•Microsoft SQL Server 2005/2008/2008R2/2012/2014/2019, performance tuning, backup and recovery, data encryption, capacity planning, understanding of database engine internals and all database objects

•Experience of loading data from different sources – xml, csv, excel, web services, different databases, MQ messages etc.

•Significant experience designing solutions following Kimball methodology and good knowledge of data modelling concepts

•Post release support of deployed BI solutions

•Experience of building reports using SSRS, PowerBI, PowerPivot, integration with SharePoint, building corporate reporting portals, KPIs, dashboards, self-service BI

Azure Cloud Data Engineer Competencies (ideal):

• Experience in Azure, in particular Data Factory, Synapse, and Databricks

• Experience in using source control, specifically GIT and deployment pipelines

• Deliver to all stages of the data engineering process

• Data ingestion, transformation, data modelling and data warehousing, and building self-service data products

• Good understanding of Data Lakes, in particular Azure Data Lake Gen2

• Experience in building robust and performant ETL processes

• Building and maintain Analysis Services databases and cubes (both multidimensional and tabular)

• Knowledge of financial markets and industry financial reporting standard

• Azure Certification will be beneficial