Develop, exploit, and maintain data products. Data Engineering teams are responsible for the delivery and operational stability of the data products built and provide ongoing support for those products. Data Engineers work within, and contribute to, the overall data development lifecycle process as part of multi-functional Agile delivery teams focused on one or more products. Data Engineers should have the following essential skills:

• Ability to shape solutions in a fit for purpose way, following the agreed principles and contribute to the overall Data Engineer development lifecycle.

• Ability to support the day-to-day testing and produce robust test plans to ensure quality solutions and the live running of data products and services.

• Ability to perform data profiling and quality measurements, ensure data quality/accuracy, knowledge of structured and unstructured data concepts, developing automated data ingest routines, workflows/mappings and data exploitation patterns and data analysis.

• Own the stability of products designed, including the on-going robustness, resilience, and stability of these products.

• Ability to identify, manage, and resolve issues/problems preventing the delivery or continuous development of products, using analytical skills to develop query solutions from specification to conclusion and implementation.

• Ability to support the growth of the team, by keeping abreast of market and industry trends, and sharing knowledge and experience with the rest of the team. Take responsibility for their own learning and development continuously improving knowledge and skills.

Typical Data Engineering Experience required:

• Knowledge and experience of Azure/AWS Cloud data solution provision.

• Proficient in SQL.

• Ability to develop and deliver complex visualisation, reporting and dashboard solutions using tools like Power BI.

• Enterprise-scale experience with ETL tools.

• Experience of data modelling and transforming raw data into datasets and extracts.

• Experience of working in a large project /scale complex organisation and knowledge of migrating legacy capabilities.

• Experience in Agile.

• Ability to analyse and collect information and evidence, identify problems and opportunities, and ensure recommendations fit with strategic business objectives.

• Experience of building team capability through role modelling, mentoring, and coaching.

• Ability to manage relationships with non-technical colleagues and can work in a collaborative, inclusive way.

Typically Data Engineer Skills required includes:

• Azure: Azure Data Factory, Data bricks, ADLS Gen2, Synapse, Purview (Desirable)

• AWS: AWS Lambda, S3, Step Functions, CloudWatch, Redshift, Glue, Event Bridge

• Languages: Python, PySpark, Scala, SQL

• Code Repository: Git / BitBucket