The Data Engineering team are extremely driven by the delivery of value into the business and seek to blend a strong technical capability with an acute business focus.
We work within an agile delivery framework supporting different workloads using both SCRUM & Kanban, and focus all our development efforts towards clearly identified business goals.
Responsibilities:
- This role will promote the available data and analytics capabilities and expertise to business unit leaders and educate them in leveraging these capabilities
- Collaborate across departments: The newly hired data engineer will need strong collaboration skills in order to work with varied stakeholders within the organization.
- Build data pipelines: Managed data pipelines consist of a series of stages through which data flows, these data pipelines must be created, maintained and optimized as workloads move from development to production for specific use cases.
- Drive Automation: The data engineer will be responsible for using innovative and modern tools, techniques and architectures to partially or completely automate the most-common, repeatable and tedious data preparation and integration tasks in order to minimize manual and error-prone processes and improve productivity.
- Educate and train
- Participate in ensuring compliance and governance during data use: It will be the responsibility of the data engineer to ensure that the data users and consumers use the data provisioned to them responsibly through data governance and compliance initiatives.
Skills:
- At least three years or more of work experience in data solutions design and development including data warehouse; ETL/ELT; and data integration.
- Delta Lakehouse architecture and associated technologies such as Databricks, Azure Data Lake, and Azure Data Factory.
- T-SQL, SparkSQL and PySpark.
- Good understanding of data modelling techniques including conceptual, logical, and physical models, and Kimball and 3NF data structures.
- Experience working with popular data discovery, analytics, and BI software tools like Power BI, Tableau, Qlik and others for semantic-layer-based data discovery.
- SQL Server BI stack. (SQL Server; SSIS).
- Good experience of working in an agile delivery framework using Azure DevOps
- Good awareness of data governance and appropriate management of risks associated with data.
