Data Engineer/Scientist

Full Job Description

Data Engineer/Scientist
London (Hybrid)
50,000-60,000 (+bens)

83DATA are partered with a leading Internet provider seeking the skills of a Data Engineer/Scientist. The successful candidate can expect to be tasked to connect data sources to pre-existing Azure data infrastructure. You will lead projects with a data centric approach, for this reason, a passion and aptitude for critical analysis of large and complex datasets is vital. The role will directly report to the Head of Data - a high degree of resilience is required to provide solutions to the executive board thus enabling data driven decisions.

Responsibilites:

• Build data engineering pipelines to ingest, transform, store, and serve high quality data for Data Scientists
• Writing and tuning complex data pipelines, workflows, and data structures.
• Identify opportunities for increasing performance, minimising costs and increase platform monitoring.
• Background of using data analysis tools and software (e.g., SQL, SAS, Python and R).
• Experience with components such as Azure Active Directory, Management Groups, Subscriptions, vNets, Route Tables, NSG's and Azure Firewalls.
• Ensuring data security and maintaining quality assurance across all systems.
• Promote a data driven culture, advocating for the use of data and analytics in decision making and process optimisation.
• Using Predictive modeling solutions for current data and generating a model to help predict future outcomes.

Requirements :

• A Computer Science/Programming Degree.
• SQL - Advanced Proficiency
• Python - Advanced Proficiency
• Experienced in Machine Learning and predictive modelling.
• Background working with consultancy services.
• Highly experienced with MS Azure cloud platforms. 3 years minimum.
• Understanding of building resilient multi-site architectures.
• Proven ability to develop and execute user retention strategies via CRM and product.
• Experience of large complex data migrations
• Proven experience in cost optimisation and performance efficiency
• Proven experience in Data Science and/or Machine Learning including an understanding of fundamental technologies and processes involved in the research and development of data science models.