As a Data Engineer you will work on implementing complex data projects with a focus on collecting, parsing, managing, analysing and visualising large sets of data to turn information into value using multiple platforms. You will work with business analysts, architects and data scientists to understand customer business problems and needs, secure the data supply chain, implement analysis solutions and visualise outcomes that support improved decision making for a customer. You will understand how to apply technologies to solve big data problems and to develop creative big data solutions.
Key Accountabilities
- Working with colleagues to understand and implement requirements
- Securing the data supply chain, understanding how data is ingested from different sources and combined / transformed into a single data set.
- Understanding how to analyse, cleanse, join and transform data.
- Implementing designed / specified solutions into the chosen platform
- Working with colleagues to ensure that the on-prem/cloud infrastructure available is capable of meeting the solution requirements.
- Planning, designing and conducting tests of the implementations, correcting errors and re-testing to achieve an acceptable result.
- Appreciate how to manage the data including; security, archiving,
structure and storage.
Key Experience and Qualifications
- Degree level education in Mathematics, Scientific, Computing or
Engineering discipline or equivalent experience
- 6+ years of experience at various levels of Data Engineering roles including 3 years in technical lead role managing end to end solution.
- Experience in designing solutions using databases and data storage technology using RDBMS (MS SQL Server)
- Experience building and optimizing Big Data data pipelines, architectures and data sets using MS Azure data management and processing components through IaaS/PaaS/SaaS implementation models implemented through custom
- Proficiency in Python scripting. Experienced in using different python modules used for data munging
- Proficiency in Pysprak
- Be up to date with data processing technology / platforms such as Spark (Databricks)
- Experience in Data Modeling for optimizing the solution performance
- Experienced in Azure DevOps
- Experience with ETL and/or data integration tool - MuleSoft
- Good understanding of infrastructure components and their fit in different types of data solutions
- Experience of designing solutions deployed on Microsoft and Linux operating systems
- Experience of working in an agile environment, within a self-organising team.