POSITION DESCRIPTION

At ESB, data sits in the centre of our business, providing insights to support better business decisions. We are looking for Data Engineers to join our growing data engineering team. If you are passionate about data and want, be part of ESBs Net Zero Strategy, leading the transition to reliable, affordable, low carbon energy, we would love you to hear from you.
The data function within ESB operates in a Hub and Spoke model, with the Hub acting as a Centre of Excellence, supporting the individual Spokes which sit directly within five business units across ESB.
The Data Engineering team is an integral part of the Analytics Hub. This team has been set up to re-invent how ESB uses its data. It will be involved in the design, build, integration, and subsequent productionising of data pipelines from various sources across all business units to facilitate the optimal use of this data by appropriate analytics consumers such as Data Scientists, Data Analysts etc.

ESSENTIAL

• Minimum 3–5 years of relevant data engineering experience, including at least 3 years developing data pipelines.
• Proficiency in ETL development using Microsoft SSIS, Azure Synapse, or Hadoop platforms.
• Strong background in data modelling and data warehousing, with expertise in Kimball or Inmon methodologies.
• Demonstrated ability to build data products incrementally and manage data sets from multiple sources.
• Skilled in query performance tuning and writing Transact SQL scripts.
• Effective communicator with strong reporting skills and a proven drive to learn new development skills.
• Creative and solutions-oriented, continually seeking improved methods, systems, or processes.

• Ensuring the successful delivery of all assigned Data Engineering work on projects across all ESB business units and their successful deployment to production, including use cases developed by our Data Science & Analytics team.
• Responsible for our data infrastructure platforms including SSIS, Azure Synapse, Cloudera.
• Responsible for building robust and scalable data models as well has helping to shape the vision and architecture of ESBs data infrastructure into the future
• Responsible for tracking the performance of our resources and growing our capability in line with business requirements.
• The development of Extract Transform and Load routines, modelling, queries, reports, and analysis.